The primary goal of this study was a comparison of grab sample, stomach tubing and feces to understand how different sampling methods will effect the microbial communities found in samples. The current “gold standard” for surveying the rumen microbiome is with a grab sample from the rument that contains both liquid and solid particles. On a commercial dairy, fecal sampling is easy to do. Stomach tube could be done with a little more time. If a fecal sample is not representative of the stomach tube, then there is no sense doing the fecal sampling as a monitor for rumen conditions. In reality, if the stomach tube and the fecal sample do not reflect the grab sample (gold standard) then neither would be used to monitor rumen microbial health (populations).
A secondary question is the decomposition of the grab sample (liquid strained & solid). The grab sample was separated into liquid strained and solid particulate by pressing the grab sample through cheese cloth to get liquid strained and solid particulate. We will have a closer look at what communites are in what parts of the grab sample.
Note that prior to running DADA2 sequences were cleaned with kneaddata and then demuliplexed and primers trimmed with cuteadapt. Code for this is available at my GitHub Page
This program infers exact amplicon sequence variants (ASVs) from amplicon data, resolving biological differences of even 1 or 2 nucleotides. This algorithum is prefered as DADA2 reports fewer false positive sequence variants than other methods report false OTUs. Note that this is a computationally expensive so its run on a cluster and then the R objects are read in.
First we will read in the data and trim ends where there is poor quality.
The next steps learn the error rates of the data and identifies unique sequences. These data are fed into the main dada2 algorithum that makes a table of ASVs. Reads are merged and chimerias removed prior to making the final ASV table. Taxaonomy was assined using the silva database.
Getting information out of DADA2 Objects.
Let’s check the sizes of the sequences as a way to determine contamination.
##
## 221 223 226 227 229 230 231 232 237 246 251 252 253 254 255
## 1 1 2 1 3 8 1 1 2 1 5 858 4510 131 6
## 256 257 263 269 270 271 275 277 281 283 285 287 292 293 294
## 1 1 2 7 24 2 1 1 1 1 12 1 7 26 1
## 342 383
## 1 1
## [1] 256.5
These sequences have a median length of 256.5 with most are less than 390bp. The sequences longer sequences may be the result of non-specific priming. We will look at this again after specific and thoughtful filtering. If long sequences remain after filtering we will look at them closer to make sure they are infact from bacterial origin.
Now we check the number of chimeras in the dataset.
## [1] 0.9795362
Here we see that 2.01% of the sequences were identified to be chimerias and were removed from the dataset. Next, we will have a look at the read stats.
## input filtered denoisedF denoisedR merged
## 282_Trim_R1.fastq.gz 9052 7645 7522 7410 6879
## 283_Trim_R1.fastq.gz 13464 11359 11216 11089 10503
## 284_Trim_R1.fastq.gz 9144 7769 7658 7584 7108
## 285_Trim_R1.fastq.gz 9372 7985 7856 7727 7211
## 286_Trim_R1.fastq.gz 11633 9828 9692 9605 9020
## 287_Trim_R1.fastq.gz 9598 8197 8048 7949 7420
## 288_Trim_R1.fastq.gz 5220 4431 4354 4290 4019
## 289_Trim_R1.fastq.gz 5475 4643 4578 4501 4235
## 290_Trim_R1.fastq.gz 11958 10168 10032 9968 9301
## 291_Trim_R1.fastq.gz 5232 4445 4382 4330 4063
## 292_Trim_R1.fastq.gz 9222 7816 7700 7586 7048
## 293_Trim_R1.fastq.gz 8496 7327 7225 7160 6789
## 294_Trim_R1.fastq.gz 5616 4744 4664 4594 4331
## 295_Trim_R1.fastq.gz 7305 6196 6095 6008 5601
## 296_Trim_R1.fastq.gz 8684 7346 7247 7115 6652
## 297_Trim_R1.fastq.gz 7593 6304 6213 6078 5683
## 298_Trim_R1.fastq.gz 11098 9374 9213 9087 8521
## 299_Trim_R1.fastq.gz 9184 7836 7704 7577 7100
## 300_Trim_R1.fastq.gz 8612 7226 7115 6969 6516
## 301_Trim_R1.fastq.gz 7719 6476 6345 6231 5827
## 302_Trim_R1.fastq.gz 6805 5725 5634 5572 5198
## 303_Trim_R1.fastq.gz 7157 6103 6008 5894 5509
## 304_Trim_R1.fastq.gz 9437 8116 7823 7844 6943
## 306_Trim_R1.fastq.gz 8613 7475 7359 7312 6933
## 307_Trim_R1.fastq.gz 5220 4588 4514 4482 4260
## 308_Trim_R1.fastq.gz 9229 7774 7643 7623 7145
## 309_Trim_R1.fastq.gz 12202 10326 10125 10016 9420
## 310_Trim_R1.fastq.gz 9933 8518 8388 8336 7893
## 311_Trim_R1.fastq.gz 13931 11779 11565 11480 10846
## 312_Trim_R1.fastq.gz 7955 6758 6643 6604 6191
## 314_Trim_R1.fastq.gz 6183 5271 5196 5116 4731
## 359_Trim_R1.fastq.gz 11088 9360 9236 9153 8597
## 360_Trim_R1.fastq.gz 11846 10163 9985 9881 9254
## 361_Trim_R1.fastq.gz 13308 11306 11124 11004 10307
## 362_Trim_R1.fastq.gz 9383 7936 7805 7761 7266
## 363_Trim_R1.fastq.gz 6851 5715 5612 5538 5182
## 365_Trim_R1.fastq.gz 6992 5982 5890 5824 5480
## 366_Trim_R1.fastq.gz 6330 5713 5597 5572 5234
## 367_Trim_R1.fastq.gz 6732 6075 5956 5948 5526
## 368_Trim_R1.fastq.gz 8080 7280 7123 7112 6699
## 369_Trim_R1.fastq.gz 16363 14678 14369 14329 13337
## 370_Trim_R1.fastq.gz 11504 10371 10027 10134 9326
## 371_Trim_R1.fastq.gz 11769 10494 10253 10253 9557
## 372_Trim_R1.fastq.gz 15193 13658 13372 13357 12485
## 373_Trim_R1.fastq.gz 14512 13010 12743 12711 11860
## 374_Trim_R1.fastq.gz 11580 10359 10154 10090 9456
## 375_Trim_R1.fastq.gz 12296 11085 10797 10768 9966
## 376_Trim_R1.fastq.gz 13002 11778 11529 11506 10744
## 378_Trim_R1.fastq.gz 13050 11829 11566 11509 10739
## 379_Trim_R1.fastq.gz 13484 11184 11022 10760 9935
## 380_Trim_R1.fastq.gz 12795 10698 10534 10299 9511
## 381_Trim_R1.fastq.gz 13125 11040 10841 10659 9902
## 382_Trim_R1.fastq.gz 21991 18506 18264 17908 16698
## 383_Trim_R1.fastq.gz 8923 7465 7362 7233 6745
## 384_Trim_R1.fastq.gz 12080 10234 10064 9874 9117
## 385_Trim_R1.fastq.gz 9747 8208 8072 7933 7441
## 386_Trim_R1.fastq.gz 16271 13550 13287 13095 12188
## 387_Trim_R1.fastq.gz 25059 21471 20099 19119 15561
## 388_Trim_R1.fastq.gz 13699 11576 11356 11247 10419
## 389_Trim_R1.fastq.gz 14755 12555 12069 12082 10761
## 390_Trim_R1.fastq.gz 2836 2461 2427 2377 2227
## 505_Trim_R1.fastq.gz 6303 5333 5231 5210 4914
## 506_Trim_R1.fastq.gz 10828 9075 8896 8819 8260
## 507_Trim_R1.fastq.gz 7388 6304 6214 6180 5849
## 508_Trim_R1.fastq.gz 4846 4195 4127 4087 3873
## 509_Trim_R1.fastq.gz 31810 27287 26782 26568 24933
## 510_Trim_R1.fastq.gz 17493 14980 14728 14579 13701
## 511_Trim_R1.fastq.gz 16696 14268 14037 13912 13125
## Fecal_kit_Trim_R1.fastq.gz 7136 6431 6213 6246 5847
## Plant_kit_Trim_R1.fastq.gz 10475 9326 9114 9144 8641
## nonchim
## 282_Trim_R1.fastq.gz 6771
## 283_Trim_R1.fastq.gz 10316
## 284_Trim_R1.fastq.gz 6997
## 285_Trim_R1.fastq.gz 7089
## 286_Trim_R1.fastq.gz 8842
## 287_Trim_R1.fastq.gz 7300
## 288_Trim_R1.fastq.gz 3946
## 289_Trim_R1.fastq.gz 4159
## 290_Trim_R1.fastq.gz 9108
## 291_Trim_R1.fastq.gz 3992
## 292_Trim_R1.fastq.gz 6894
## 293_Trim_R1.fastq.gz 6690
## 294_Trim_R1.fastq.gz 4234
## 295_Trim_R1.fastq.gz 5501
## 296_Trim_R1.fastq.gz 6513
## 297_Trim_R1.fastq.gz 5571
## 298_Trim_R1.fastq.gz 8348
## 299_Trim_R1.fastq.gz 6987
## 300_Trim_R1.fastq.gz 6354
## 301_Trim_R1.fastq.gz 5710
## 302_Trim_R1.fastq.gz 5085
## 303_Trim_R1.fastq.gz 5411
## 304_Trim_R1.fastq.gz 6777
## 306_Trim_R1.fastq.gz 6859
## 307_Trim_R1.fastq.gz 4205
## 308_Trim_R1.fastq.gz 7033
## 309_Trim_R1.fastq.gz 9302
## 310_Trim_R1.fastq.gz 7800
## 311_Trim_R1.fastq.gz 10718
## 312_Trim_R1.fastq.gz 6091
## 314_Trim_R1.fastq.gz 4646
## 359_Trim_R1.fastq.gz 8447
## 360_Trim_R1.fastq.gz 9124
## 361_Trim_R1.fastq.gz 10133
## 362_Trim_R1.fastq.gz 7114
## 363_Trim_R1.fastq.gz 5086
## 365_Trim_R1.fastq.gz 5373
## 366_Trim_R1.fastq.gz 5108
## 367_Trim_R1.fastq.gz 5396
## 368_Trim_R1.fastq.gz 6523
## 369_Trim_R1.fastq.gz 12909
## 370_Trim_R1.fastq.gz 9068
## 371_Trim_R1.fastq.gz 9325
## 372_Trim_R1.fastq.gz 12123
## 373_Trim_R1.fastq.gz 11506
## 374_Trim_R1.fastq.gz 9155
## 375_Trim_R1.fastq.gz 9677
## 376_Trim_R1.fastq.gz 10412
## 378_Trim_R1.fastq.gz 10388
## 379_Trim_R1.fastq.gz 9705
## 380_Trim_R1.fastq.gz 9308
## 381_Trim_R1.fastq.gz 9710
## 382_Trim_R1.fastq.gz 16323
## 383_Trim_R1.fastq.gz 6608
## 384_Trim_R1.fastq.gz 8923
## 385_Trim_R1.fastq.gz 7279
## 386_Trim_R1.fastq.gz 11864
## 387_Trim_R1.fastq.gz 14877
## 388_Trim_R1.fastq.gz 10229
## 389_Trim_R1.fastq.gz 10542
## 390_Trim_R1.fastq.gz 2189
## 505_Trim_R1.fastq.gz 4867
## 506_Trim_R1.fastq.gz 8152
## 507_Trim_R1.fastq.gz 5755
## 508_Trim_R1.fastq.gz 3833
## 509_Trim_R1.fastq.gz 24624
## 510_Trim_R1.fastq.gz 13462
## 511_Trim_R1.fastq.gz 12964
## Fecal_kit_Trim_R1.fastq.gz 5807
## Plant_kit_Trim_R1.fastq.gz 8562
This shows the library sizes of the samples and how many reads were removed at each step. There is 7.4796110^{5} cleaned reads that entered the DADA2 pipeline. We will now get read stats for the input ASVs.
## [1] 747961
We compare this to the read stats for the final libraries.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 5607 taxa and 70 samples ]
## sample_data() Sample Data: [ 70 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]
Currently, we are starting with 5,607 ASVs from 70 samples
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 5607 taxa and 68 samples ]
## sample_data() Sample Data: [ 68 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]
First, we remove the kit samples to bring us down to 68 samples. We will look at these again later. We will also remove ASVs that aren’t present in any samples.
There was no empty samples or taxa which is what we want. Also, there was 16 ASVs that weren’t in any sample and were removed.
To start cleaning the data we will at the number of ASVs assigned to each phylum.
##
## Actinobacteria Bacteroidetes Chloroflexi
## 96 1257 39
## Cyanobacteria Deferribacteres Elusimicrobia
## 74 1 16
## Epsilonbacteraeota Euryarchaeota Fibrobacteres
## 2 44 39
## Firmicutes Fusobacteria Gemmatimonadetes
## 3095 4 1
## Kiritimatiellaeota Lentisphaerae Patescibacteria
## 180 31 14
## Planctomycetes Proteobacteria Spirochaetes
## 15 222 138
## Synergistetes Tenericutes Verrucomicrobia
## 6 188 35
## <NA>
## 94
Next we will count what samples have the ASVs that aren’t assigned to a phylum.
There are 94 ASVs that weren’t able to be assigned to a phylum. These unassigned taxa are found in all sample types with most of the unassigned ASVs in solid samples. NOTE that the sum column is reads not the number of ASVs! We next made a fasta file from the phyloseq object with these unknown taxa so that we can blast it later.
Getting back to our orginal phyloseq object: the 94 AVSs that weren’t assigned to a phyla were removed for analysis. This leaves 5,497 ASVs.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 5497 taxa and 68 samples ]
## sample_data() Sample Data: [ 68 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 5497 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 5497 tips and 5495 internal nodes ]
Next we will compute the total and average prevalences of the ASVs in each phylum. We are defining prevalence as the number of samples in which a taxon appears at least once.
| Phylum | 1 | 2 |
|---|---|---|
| Actinobacteria | 19.78125 | 1899 |
| Bacteroidetes | 22.49483 | 28276 |
| Chloroflexi | 28.66667 | 1118 |
| Cyanobacteria | 14.45946 | 1070 |
| Deferribacteres | 1.00000 | 1 |
| Elusimicrobia | 23.43750 | 375 |
| Epsilonbacteraeota | 19.00000 | 38 |
| Euryarchaeota | 31.36364 | 1380 |
| Fibrobacteres | 31.00000 | 1209 |
| Firmicutes | 22.81874 | 70624 |
| Fusobacteria | 9.50000 | 38 |
| Gemmatimonadetes | 1.00000 | 1 |
| Kiritimatiellaeota | 19.97778 | 3596 |
| Lentisphaerae | 15.12903 | 469 |
| Patescibacteria | 26.00000 | 364 |
| Planctomycetes | 20.06667 | 301 |
| Proteobacteria | 15.32432 | 3402 |
| Spirochaetes | 21.03623 | 2903 |
| Synergistetes | 19.50000 | 117 |
| Tenericutes | 19.53191 | 3672 |
| Verrucomicrobia | 18.42857 | 645 |
Here we see that Deferribacteres and Gemmatimonadetes ASVs only has one feature so we’ll just looking into this real quick.
## [1] "Stomach Tube"
## OTU Table: [1 taxa and 1 samples]
## taxa are rows
## 282
## ASV_5560 3
## [1] "Feces"
## OTU Table: [1 taxa and 1 samples]
## taxa are rows
## 370
## ASV_5602 2
The phylum Deferribacteres are only in Fecal samples (2 reads) and and Gemmatimonadetes are only in Stomach Tube samples (3 reads). This suggest these groups might be important for comparing sample types, thus we will leave reads assigned to these phyla in the dataset despite their low prevelance.
Lastly, we’ll check to see if chloroplasts and Mitochondria are in the data set and remove them.
After removing chloroplasts and mitochondria there is 5,485 ASVs left.
As we have seen previously, there are 5485 ASVs in the dataset. This is composed of 21 phyla, 78 Orders, 116 Families and 293 Genera.
5393 ASVs didn’t have species assigned. Only 1.68% of taxa had species assigned. For genera, 1796 ASVs didn’t have a genera assigned. Only 67.3% of taxa had genera assigned.
| Phylum | #ASVs with no species assignment | Total ASVs | Percent Unassigned |
|---|---|---|---|
| Actinobacteria | 90 | 96 | 93.75000 |
| Bacteroidetes | 1244 | 1257 | 98.96579 |
| Chloroflexi | 39 | 39 | 100.00000 |
| Cyanobacteria | 65 | 65 | 100.00000 |
| Deferribacteres | 1 | 1 | 100.00000 |
| Elusimicrobia | 16 | 16 | 100.00000 |
| Epsilonbacteraeota | 2 | 2 | 100.00000 |
| Euryarchaeota | 44 | 44 | 100.00000 |
| Fibrobacteres | 34 | 39 | 87.17949 |
| Firmicutes | 3046 | 3095 | 98.41680 |
| Fusobacteria | 1 | 4 | 25.00000 |
| Gemmatimonadetes | 1 | 1 | 100.00000 |
| Kiritimatiellaeota | 180 | 180 | 100.00000 |
| Lentisphaerae | 31 | 31 | 100.00000 |
| Patescibacteria | 14 | 14 | 100.00000 |
| Planctomycetes | 15 | 15 | 100.00000 |
| Proteobacteria | 207 | 219 | 94.52055 |
| Spirochaetes | 135 | 138 | 97.82609 |
| Synergistetes | 6 | 6 | 100.00000 |
| Tenericutes | 188 | 188 | 100.00000 |
| Verrucomicrobia | 34 | 35 | 97.14286 |
This table gives the frequencing and percent of ASVs not assigned to species and their phyla. This really speaks to the limitations of the methods used here to be able to give species level assigments.
This table gives the frequencing and percent of ASVs not assigned to genus and their phyla.
There are 86 singletons (20), doubletons (37) or tripletons (29). This looks pretty good and indicates that filtering was not excessive nor was a large enough part of the data to be suspicious about. We will need these for diversity metrics.
For the last part of our cleaning process we will graph out the prevalance of ASVs assigned to each phylum.
Before moving on we will look again at the read stats to check that we still don’t have reads that are too long in the dataset.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 5485 taxa and 68 samples ]
## sample_data() Sample Data: [ 68 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 5485 taxa by 7 taxonomic ranks ]
##
## 229 230 232 246 252 253 254 255 263 269 270 271 281 287 294
## 3 7 1 1 851 4449 129 6 2 7 23 2 1 1 1
## 342
## 1
Looks like we now only have one sample that is greater than 300bp let’s see what it is.
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Archaea"
## Phylum
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Euryarchaeota"
## Class
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteria"
## Order
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriales"
## Family
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriaceae"
## Genus
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobrevibacter"
## Species
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG NA
As this large sequence is a Methanobrevibacter and this is a common rumen bacteria its expected to be here and will be left in the data set.
As the first part of the exploratory analysis we will look the general relative abundances of phyla across sample types.
| Sample_Type | Phylum | mean | sd | sem | |
|---|---|---|---|---|---|
| 94 | Solid | Firmicutes | 67.171193 | 1.89788 | 0.547872 |
| 115 | Stomach Tube | Firmicutes | 64.680196 | 7.64829 | 2.207872 |
| 31 | Grab Sample | Firmicutes | 64.309812 | 6.22378 | 1.796650 |
| 10 | Feces | Firmicutes | 61.237127 | 3.58700 | 1.035479 |
| 73 | Liquid Unstrained | Firmicutes | 55.214891 | 6.56683 | 2.321726 |
| 52 | Liquid Strained | Firmicutes | 43.521396 | 3.83594 | 1.107340 |
| 44 | Liquid Strained | Bacteroidetes | 33.325984 | 3.48697 | 1.006602 |
| 2 | Feces | Bacteroidetes | 32.089477 | 3.22568 | 0.931172 |
| 65 | Liquid Unstrained | Bacteroidetes | 26.470699 | 2.42579 | 0.857646 |
| 107 | Stomach Tube | Bacteroidetes | 20.863182 | 4.86305 | 1.403841 |
| 86 | Solid | Bacteroidetes | 20.221741 | 2.76979 | 0.799571 |
| 23 | Grab Sample | Bacteroidetes | 19.959058 | 2.22827 | 0.643245 |
| 55 | Liquid Strained | Kiritimatiellaeota | 6.959357 | 1.43120 | 0.413151 |
| 39 | Grab Sample | Spirochaetes | 4.123484 | 7.67724 | 2.216229 |
| 76 | Liquid Unstrained | Kiritimatiellaeota | 3.954869 | 2.05528 | 0.726650 |
| 59 | Liquid Strained | Proteobacteria | 3.891003 | 1.39286 | 0.402083 |
| 113 | Stomach Tube | Euryarchaeota | 3.329381 | 1.35194 | 0.390270 |
| 92 | Solid | Euryarchaeota | 3.167559 | 1.78381 | 0.514941 |
| 80 | Liquid Unstrained | Proteobacteria | 3.012016 | 1.47040 | 0.519864 |
| 29 | Grab Sample | Euryarchaeota | 2.518253 | 0.87016 | 0.251193 |
| 71 | Liquid Unstrained | Euryarchaeota | 2.360323 | 1.42703 | 0.504532 |
| 60 | Liquid Strained | Spirochaetes | 2.259901 | 0.81533 | 0.235364 |
| 50 | Liquid Strained | Euryarchaeota | 2.202896 | 1.40978 | 0.406970 |
| 30 | Grab Sample | Fibrobacteres | 2.182511 | 0.52162 | 0.150579 |
| 62 | Liquid Strained | Tenericutes | 2.007239 | 0.41986 | 0.121202 |
| 81 | Liquid Unstrained | Spirochaetes | 1.937928 | 0.95423 | 0.337371 |
| 83 | Liquid Unstrained | Tenericutes | 1.883149 | 0.54376 | 0.192247 |
| 118 | Stomach Tube | Kiritimatiellaeota | 1.850052 | 1.30901 | 0.377879 |
| 122 | Stomach Tube | Proteobacteria | 1.813390 | 0.85311 | 0.246273 |
| 51 | Liquid Strained | Fibrobacteres | 1.790122 | 0.68267 | 0.197069 |
| 106 | Stomach Tube | Actinobacteria | 1.593072 | 0.44466 | 0.128362 |
| 38 | Grab Sample | Proteobacteria | 1.577367 | 0.39181 | 0.113107 |
| 125 | Stomach Tube | Tenericutes | 1.562888 | 0.47927 | 0.138353 |
| 101 | Solid | Proteobacteria | 1.514819 | 0.53489 | 0.154410 |
| 93 | Solid | Fibrobacteres | 1.440196 | 0.59696 | 0.172328 |
| 21 | Feces | Verrucomicrobia | 1.330008 | 0.53676 | 0.154950 |
| 41 | Grab Sample | Tenericutes | 1.327798 | 0.18652 | 0.053844 |
| 85 | Solid | Actinobacteria | 1.218782 | 0.30407 | 0.087779 |
| 102 | Solid | Spirochaetes | 1.117817 | 0.37786 | 0.109078 |
| 123 | Stomach Tube | Spirochaetes | 1.110958 | 0.63550 | 0.183454 |
| 22 | Grab Sample | Actinobacteria | 1.097541 | 0.22664 | 0.065427 |
| 104 | Solid | Tenericutes | 1.083357 | 0.17849 | 0.051527 |
| 17 | Feces | Proteobacteria | 1.076418 | 0.31832 | 0.091890 |
| 20 | Feces | Tenericutes | 0.974926 | 0.22835 | 0.065918 |
| 34 | Grab Sample | Kiritimatiellaeota | 0.949299 | 0.11497 | 0.033190 |
| 72 | Liquid Unstrained | Fibrobacteres | 0.924121 | 0.57314 | 0.202635 |
| 64 | Liquid Unstrained | Actinobacteria | 0.924064 | 0.33227 | 0.117476 |
| 46 | Liquid Strained | Cyanobacteria | 0.886615 | 0.36020 | 0.103981 |
| 13 | Feces | Kiritimatiellaeota | 0.842224 | 0.34891 | 0.100721 |
| 97 | Solid | Kiritimatiellaeota | 0.811684 | 0.13214 | 0.038147 |
| 99 | Solid | Patescibacteria | 0.696159 | 0.18816 | 0.054316 |
| 43 | Liquid Strained | Actinobacteria | 0.687316 | 0.30537 | 0.088154 |
| 87 | Solid | Chloroflexi | 0.680062 | 0.19086 | 0.055096 |
| 56 | Liquid Strained | Lentisphaerae | 0.671255 | 0.19280 | 0.055656 |
| 108 | Stomach Tube | Chloroflexi | 0.663903 | 0.15329 | 0.044252 |
| 8 | Feces | Euryarchaeota | 0.636827 | 0.34124 | 0.098507 |
| 67 | Liquid Unstrained | Cyanobacteria | 0.622941 | 0.41690 | 0.147396 |
| 77 | Liquid Unstrained | Lentisphaerae | 0.620633 | 0.41150 | 0.145487 |
| 126 | Stomach Tube | Verrucomicrobia | 0.609821 | 0.21143 | 0.061034 |
| 24 | Grab Sample | Chloroflexi | 0.584714 | 0.13518 | 0.039024 |
| 66 | Liquid Unstrained | Chloroflexi | 0.544889 | 0.08668 | 0.030645 |
| 84 | Liquid Unstrained | Verrucomicrobia | 0.540529 | 0.14486 | 0.051215 |
| 36 | Grab Sample | Patescibacteria | 0.531587 | 0.17283 | 0.049892 |
| 78 | Liquid Unstrained | Patescibacteria | 0.525094 | 0.16369 | 0.057872 |
| 57 | Liquid Strained | Patescibacteria | 0.480896 | 0.12887 | 0.037201 |
| 4 | Feces | Cyanobacteria | 0.449117 | 0.13271 | 0.038309 |
| 119 | Stomach Tube | Lentisphaerae | 0.442976 | 0.32682 | 0.094345 |
| 45 | Liquid Strained | Chloroflexi | 0.421857 | 0.11367 | 0.032813 |
| 1 | Feces | Actinobacteria | 0.407788 | 0.11409 | 0.032934 |
| 63 | Liquid Strained | Verrucomicrobia | 0.392914 | 0.11300 | 0.032619 |
| 120 | Stomach Tube | Patescibacteria | 0.365494 | 0.15142 | 0.043712 |
| 48 | Liquid Strained | Elusimicrobia | 0.363036 | 0.20188 | 0.058278 |
| 114 | Stomach Tube | Fibrobacteres | 0.354001 | 0.23941 | 0.069110 |
| 105 | Solid | Verrucomicrobia | 0.339158 | 0.06796 | 0.019618 |
| 42 | Grab Sample | Verrucomicrobia | 0.330473 | 0.10189 | 0.029413 |
| 18 | Feces | Spirochaetes | 0.328016 | 0.21602 | 0.062360 |
| 69 | Liquid Unstrained | Elusimicrobia | 0.317035 | 0.18254 | 0.064539 |
| 109 | Stomach Tube | Cyanobacteria | 0.274073 | 0.25401 | 0.073326 |
| 14 | Feces | Lentisphaerae | 0.237553 | 0.18456 | 0.053277 |
| 16 | Feces | Planctomycetes | 0.195166 | 0.07189 | 0.020753 |
| 111 | Stomach Tube | Elusimicrobia | 0.156546 | 0.13165 | 0.038005 |
| 90 | Solid | Elusimicrobia | 0.151592 | 0.08210 | 0.023700 |
| 25 | Grab Sample | Cyanobacteria | 0.139923 | 0.06311 | 0.018219 |
| 116 | Stomach Tube | Fusobacteria | 0.130143 | 0.11210 | 0.032361 |
| 121 | Stomach Tube | Planctomycetes | 0.126690 | 0.04305 | 0.012427 |
| 103 | Solid | Synergistetes | 0.121142 | 0.03615 | 0.010437 |
| 27 | Grab Sample | Elusimicrobia | 0.111197 | 0.04869 | 0.014056 |
| 100 | Solid | Planctomycetes | 0.102944 | 0.01891 | 0.005458 |
| 6 | Feces | Elusimicrobia | 0.097389 | 0.05545 | 0.016006 |
| 37 | Grab Sample | Planctomycetes | 0.096631 | 0.04228 | 0.012205 |
| 88 | Solid | Cyanobacteria | 0.095623 | 0.06059 | 0.017491 |
| 79 | Liquid Unstrained | Planctomycetes | 0.087836 | 0.03479 | 0.012301 |
| 35 | Grab Sample | Lentisphaerae | 0.077359 | 0.04240 | 0.012241 |
| 40 | Grab Sample | Synergistetes | 0.076985 | 0.04797 | 0.013848 |
| 58 | Liquid Strained | Planctomycetes | 0.064471 | 0.03202 | 0.009243 |
| 98 | Solid | Lentisphaerae | 0.056500 | 0.02380 | 0.006872 |
| 124 | Stomach Tube | Synergistetes | 0.052609 | 0.04184 | 0.012079 |
| 82 | Liquid Unstrained | Synergistetes | 0.048419 | 0.01954 | 0.006910 |
| 61 | Liquid Strained | Synergistetes | 0.045930 | 0.02969 | 0.008572 |
| 7 | Feces | Epsilonbacteraeota | 0.036546 | 0.02753 | 0.007948 |
| 3 | Feces | Chloroflexi | 0.033252 | 0.01365 | 0.003940 |
| 49 | Liquid Strained | Epsilonbacteraeota | 0.020465 | 0.02449 | 0.007068 |
| 9 | Feces | Fibrobacteres | 0.017672 | 0.01711 | 0.004938 |
| 112 | Stomach Tube | Epsilonbacteraeota | 0.016921 | 0.02402 | 0.006934 |
| 53 | Liquid Strained | Fusobacteria | 0.007350 | 0.01514 | 0.004369 |
| 91 | Solid | Epsilonbacteraeota | 0.006537 | 0.00899 | 0.002595 |
| 70 | Liquid Unstrained | Epsilonbacteraeota | 0.005759 | 0.00860 | 0.003042 |
| 15 | Feces | Patescibacteria | 0.005358 | 0.00988 | 0.002851 |
| 74 | Liquid Unstrained | Fusobacteria | 0.004807 | 0.01090 | 0.003854 |
| 117 | Stomach Tube | Gemmatimonadetes | 0.003704 | 0.01283 | 0.003704 |
| 95 | Solid | Fusobacteria | 0.003135 | 0.00469 | 0.001353 |
| 32 | Grab Sample | Fusobacteria | 0.003029 | 0.00707 | 0.002042 |
| 28 | Grab Sample | Epsilonbacteraeota | 0.002979 | 0.00739 | 0.002133 |
| 11 | Feces | Fusobacteria | 0.002610 | 0.00473 | 0.001365 |
| 5 | Feces | Deferribacteres | 0.001839 | 0.00637 | 0.001839 |
| 19 | Feces | Synergistetes | 0.000688 | 0.00238 | 0.000688 |
| 12 | Feces | Gemmatimonadetes | 0.000000 | 0.00000 | 0.000000 |
| 26 | Grab Sample | Deferribacteres | 0.000000 | 0.00000 | 0.000000 |
| 33 | Grab Sample | Gemmatimonadetes | 0.000000 | 0.00000 | 0.000000 |
| 47 | Liquid Strained | Deferribacteres | 0.000000 | 0.00000 | 0.000000 |
| 54 | Liquid Strained | Gemmatimonadetes | 0.000000 | 0.00000 | 0.000000 |
| 68 | Liquid Unstrained | Deferribacteres | 0.000000 | 0.00000 | 0.000000 |
| 75 | Liquid Unstrained | Gemmatimonadetes | 0.000000 | 0.00000 | 0.000000 |
| 89 | Solid | Deferribacteres | 0.000000 | 0.00000 | 0.000000 |
| 96 | Solid | Gemmatimonadetes | 0.000000 | 0.00000 | 0.000000 |
| 110 | Stomach Tube | Deferribacteres | 0.000000 | 0.00000 | 0.000000 |
We will look at relative abundance of Phyla in certain sample types. First, grab samples.
Next, we examine the relative abundance of Phyla in only fecal samples.
These are the phyla found in all samples sorted by decending order of mean relative abundance.
We will have a look to see if any phyla only present in only feces or only in stomach tube samples.
Deferribacteres Was only found in fecal samples and Gemmatimonadetes was only found in stomach tube samples.
This confirms what we say earlier and we didn’t identify any other phyla that are only present in these sample types.
Next we will graph out some of the different phyla based on their abundance ranges.
This is a graph of the major phyla, defined as those present at an abundance greater than 3% relative abundance, in rumen samples. Next we will graph phyla less than 3% relative abundance.
This is a graph of the “minor” phyla, defined as present at an abundance below 3%, in rumen samples. I also made an interactive version of this graph to put a link for in the manuscript.
You can access the interactive figure here.Below is Figure 1 A & B.
## Saving 180 x 152 mm image
We will do the create the same graphs at the family level as well.
This is a table of the relative abundances of families in all sample types.
| Sample_Type | Family | mean | sd | sem | |
|---|---|---|---|---|---|
| 96 | Feces | Ruminococcaceae | 40.662043 | 2.17531 | 0.627959 |
| 171 | Grab Sample | Lachnospiraceae | 25.909379 | 2.13026 | 0.614953 |
| 516 | Solid | Lachnospiraceae | 24.978741 | 2.41347 | 0.696708 |
| 631 | Stomach Tube | Lachnospiraceae | 23.893818 | 3.88265 | 1.120824 |
| 320 | Liquid Strained | Prevotellaceae | 23.776220 | 3.98548 | 1.150509 |
| 556 | Solid | Ruminococcaceae | 19.590277 | 0.60315 | 0.174115 |
| 487 | Solid | Christensenellaceae | 19.580047 | 1.68893 | 0.487552 |
| 602 | Stomach Tube | Christensenellaceae | 18.574572 | 1.73189 | 0.499955 |
| 441 | Liquid Unstrained | Ruminococcaceae | 18.461506 | 1.59136 | 0.562629 |
| 142 | Grab Sample | Christensenellaceae | 18.085232 | 2.72055 | 0.785356 |
| 671 | Stomach Tube | Ruminococcaceae | 17.918312 | 1.45935 | 0.421278 |
| 401 | Liquid Unstrained | Lachnospiraceae | 17.835313 | 2.41513 | 0.853876 |
| 211 | Grab Sample | Ruminococcaceae | 17.481760 | 2.51743 | 0.726720 |
| 372 | Liquid Unstrained | Christensenellaceae | 16.812558 | 2.68812 | 0.950394 |
| 435 | Liquid Unstrained | Prevotellaceae | 16.146729 | 2.34486 | 0.829034 |
| 95 | Feces | Rikenellaceae | 15.692367 | 2.04158 | 0.589352 |
| 326 | Liquid Strained | Ruminococcaceae | 15.458665 | 1.76966 | 0.510857 |
| 286 | Liquid Strained | Lachnospiraceae | 15.089913 | 1.75205 | 0.505772 |
| 257 | Liquid Strained | Christensenellaceae | 12.142322 | 1.44194 | 0.416253 |
| 665 | Stomach Tube | Prevotellaceae | 10.533860 | 3.46172 | 0.999311 |
| 550 | Solid | Prevotellaceae | 9.172494 | 1.41162 | 0.407499 |
| 205 | Grab Sample | Prevotellaceae | 8.656660 | 1.49577 | 0.431791 |
| 555 | Solid | Rikenellaceae | 7.756655 | 1.17414 | 0.338944 |
| 56 | Feces | Lachnospiraceae | 7.718256 | 1.85419 | 0.535258 |
| 27 | Feces | Christensenellaceae | 7.483265 | 1.06576 | 0.307660 |
| 210 | Grab Sample | Rikenellaceae | 7.475779 | 1.14093 | 0.329358 |
| 11 | Feces | Bacteroidaceae | 7.403751 | 0.87114 | 0.251478 |
| 670 | Stomach Tube | Rikenellaceae | 7.375575 | 1.78391 | 0.514971 |
| 440 | Liquid Unstrained | Rikenellaceae | 6.348289 | 1.01506 | 0.358878 |
| 90 | Feces | Prevotellaceae | 6.258670 | 1.21983 | 0.352134 |
| 325 | Liquid Strained | Rikenellaceae | 5.326237 | 1.30835 | 0.377688 |
| 217 | Grab Sample | Spirochaetaceae | 4.279276 | 8.11607 | 2.342907 |
| 277 | Liquid Strained | F082 | 4.166934 | 0.94223 | 0.271998 |
| 638 | Stomach Tube | Methanobacteriaceae | 3.290438 | 1.39475 | 0.402629 |
| 523 | Solid | Methanobacteriaceae | 3.006646 | 1.84641 | 0.533014 |
| 86 | Feces | Peptostreptococcaceae | 2.894522 | 0.89910 | 0.259548 |
| 392 | Liquid Unstrained | F082 | 2.882237 | 0.41067 | 0.145192 |
| 624 | Stomach Tube | Family_XIII | 2.719298 | 0.57073 | 0.164756 |
| 509 | Solid | Family_XIII | 2.651126 | 0.58246 | 0.168141 |
| 49 | Feces | Family_XIII | 2.577243 | 0.65975 | 0.190455 |
| 178 | Grab Sample | Methanobacteriaceae | 2.464815 | 0.92852 | 0.268041 |
| 164 | Grab Sample | Family_XIII | 2.446497 | 0.58196 | 0.167996 |
| 332 | Liquid Strained | Spirochaetaceae | 2.408240 | 0.91161 | 0.263159 |
| 408 | Liquid Unstrained | Methanobacteriaceae | 2.287936 | 1.46200 | 0.516895 |
| 165 | Grab Sample | Fibrobacteraceae | 2.286694 | 0.54644 | 0.157744 |
| 293 | Liquid Strained | Methanobacteriaceae | 2.243293 | 1.52734 | 0.440906 |
| 342 | Liquid Strained | Veillonellaceae | 2.113366 | 0.56986 | 0.164503 |
| 394 | Liquid Unstrained | Family_XIII | 2.030927 | 0.50719 | 0.179319 |
| 447 | Liquid Unstrained | Spirochaetaceae | 2.023389 | 1.06782 | 0.377533 |
| 280 | Liquid Strained | Fibrobacteraceae | 2.017938 | 0.79045 | 0.228183 |
| 622 | Stomach Tube | F082 | 1.883605 | 0.94966 | 0.274142 |
| 250 | Liquid Strained | Burkholderiaceae | 1.613253 | 1.14707 | 0.331132 |
| 162 | Grab Sample | F082 | 1.573685 | 0.31899 | 0.092086 |
| 457 | Liquid Unstrained | Veillonellaceae | 1.558952 | 0.80191 | 0.283518 |
| 336 | Liquid Strained | Succinivibrionaceae | 1.543685 | 0.60789 | 0.175483 |
| 620 | Stomach Tube | Erysipelotrichaceae | 1.537342 | 0.29198 | 0.084288 |
| 510 | Solid | Fibrobacteraceae | 1.505930 | 0.62518 | 0.180473 |
| 507 | Solid | F082 | 1.479020 | 0.40472 | 0.116833 |
| 5 | Feces | Akkermansiaceae | 1.399232 | 0.56693 | 0.163658 |
| 243 | Liquid Strained | Bacteroidales_RF16_group | 1.369223 | 0.39137 | 0.112979 |
| 308 | Liquid Strained | p-251-o5 | 1.337976 | 0.62608 | 0.180735 |
| 279 | Liquid Strained | Family_XIII | 1.318429 | 0.37085 | 0.107056 |
| 365 | Liquid Unstrained | Burkholderiaceae | 1.116637 | 0.97066 | 0.343179 |
| 562 | Solid | Spirochaetaceae | 1.100219 | 0.34829 | 0.100541 |
| 677 | Stomach Tube | Spirochaetaceae | 1.099645 | 0.62883 | 0.181527 |
| 680 | Stomach Tube | Streptococcaceae | 1.095366 | 0.92407 | 0.266756 |
| 275 | Liquid Strained | Erysipelotrichaceae | 1.070523 | 0.37997 | 0.109687 |
| 390 | Liquid Unstrained | Erysipelotrichaceae | 1.065354 | 0.19851 | 0.070183 |
| 451 | Liquid Unstrained | Succinivibrionaceae | 1.052210 | 0.67959 | 0.240271 |
| 237 | Liquid Strained | Anaeroplasmataceae | 1.026677 | 0.33767 | 0.097476 |
| 395 | Liquid Unstrained | Fibrobacteraceae | 1.017878 | 0.65786 | 0.232590 |
| 583 | Stomach Tube | Atopobiaceae | 1.006651 | 0.40293 | 0.116316 |
| 463 | Solid | Acidaminococcaceae | 0.980055 | 0.25973 | 0.074976 |
| 160 | Grab Sample | Erysipelotrichaceae | 0.972573 | 0.17214 | 0.049692 |
| 352 | Liquid Unstrained | Anaeroplasmataceae | 0.951233 | 0.35690 | 0.126184 |
| 358 | Liquid Unstrained | Bacteroidales_RF16_group | 0.869041 | 0.28465 | 0.100640 |
| 423 | Liquid Unstrained | p-251-o5 | 0.851984 | 0.25395 | 0.089786 |
| 505 | Solid | Erysipelotrichaceae | 0.840776 | 0.18666 | 0.053883 |
| 45 | Feces | Erysipelotrichaceae | 0.825341 | 0.17601 | 0.050811 |
| 227 | Grab Sample | Veillonellaceae | 0.748046 | 0.18592 | 0.053671 |
| 79 | Feces | p-2534-18B5_gut_group | 0.745844 | 0.49756 | 0.143633 |
| 466 | Solid | Anaerolineaceae | 0.710695 | 0.19884 | 0.057401 |
| 581 | Stomach Tube | Anaerolineaceae | 0.699699 | 0.15876 | 0.045830 |
| 13 | Feces | Bacteroidales_RF16_group | 0.681372 | 0.16245 | 0.046895 |
| 348 | Liquid Unstrained | Acidaminococcaceae | 0.679111 | 0.18720 | 0.066184 |
| 687 | Stomach Tube | Veillonellaceae | 0.677002 | 0.41223 | 0.119001 |
| 341 | Liquid Strained | vadinBE97 | 0.668188 | 0.20766 | 0.059946 |
| 357 | Liquid Unstrained | Bacteroidales_BS11_gut_group | 0.647920 | 0.23197 | 0.082014 |
| 353 | Liquid Unstrained | Atopobiaceae | 0.644468 | 0.30347 | 0.107292 |
| 242 | Liquid Strained | Bacteroidales_BS11_gut_group | 0.636461 | 0.16085 | 0.046432 |
| 127 | Grab Sample | Bacteroidales_BS11_gut_group | 0.633199 | 0.16352 | 0.047204 |
| 472 | Solid | Bacteroidales_BS11_gut_group | 0.626981 | 0.16838 | 0.048607 |
| 456 | Liquid Unstrained | vadinBE97 | 0.619314 | 0.42255 | 0.149393 |
| 121 | Grab Sample | Anaerolineaceae | 0.612631 | 0.14162 | 0.040881 |
| 63 | Feces | Methanobacteriaceae | 0.596446 | 0.37468 | 0.108160 |
| 351 | Liquid Unstrained | Anaerolineaceae | 0.590020 | 0.08645 | 0.030563 |
| 118 | Grab Sample | Acidaminococcaceae | 0.577466 | 0.10489 | 0.030280 |
| 500 | Solid | Eggerthellaceae | 0.566750 | 0.12475 | 0.036012 |
| 36 | Feces | Desulfovibrionaceae | 0.560810 | 0.27123 | 0.078297 |
| 496 | Solid | Desulfovibrionaceae | 0.559735 | 0.21469 | 0.061977 |
| 123 | Grab Sample | Atopobiaceae | 0.556082 | 0.11200 | 0.032332 |
| 582 | Stomach Tube | Anaeroplasmataceae | 0.550660 | 0.27169 | 0.078429 |
| 193 | Grab Sample | p-251-o5 | 0.534799 | 0.26332 | 0.076013 |
| 468 | Solid | Atopobiaceae | 0.533660 | 0.15493 | 0.044724 |
| 151 | Grab Sample | Desulfovibrionaceae | 0.530917 | 0.17663 | 0.050988 |
| 238 | Liquid Strained | Atopobiaceae | 0.524360 | 0.29423 | 0.084937 |
| 611 | Stomach Tube | Desulfovibrionaceae | 0.523125 | 0.17801 | 0.051387 |
| 578 | Stomach Tube | Acidaminococcaceae | 0.520036 | 0.17769 | 0.051296 |
| 85 | Feces | Peptococcaceae | 0.510863 | 0.10803 | 0.031186 |
| 530 | Solid | Muribaculaceae | 0.501963 | 0.06935 | 0.020019 |
| 233 | Liquid Strained | Acidaminococcaceae | 0.482755 | 0.14870 | 0.042927 |
| 615 | Stomach Tube | Eggerthellaceae | 0.478785 | 0.15600 | 0.045032 |
| 155 | Grab Sample | Eggerthellaceae | 0.475405 | 0.13575 | 0.039188 |
| 236 | Liquid Strained | Anaerolineaceae | 0.473437 | 0.12683 | 0.036612 |
| 185 | Grab Sample | Muribaculaceae | 0.463656 | 0.09160 | 0.026444 |
| 587 | Stomach Tube | Bacteroidales_BS11_gut_group | 0.447419 | 0.23030 | 0.066483 |
| 686 | Stomach Tube | vadinBE97 | 0.435754 | 0.34089 | 0.098407 |
| 588 | Stomach Tube | Bacteroidales_RF16_group | 0.420013 | 0.26444 | 0.076336 |
| 381 | Liquid Unstrained | Desulfovibrionaceae | 0.392658 | 0.11058 | 0.039095 |
| 221 | Grab Sample | Succinivibrionaceae | 0.380597 | 0.18977 | 0.054781 |
| 625 | Stomach Tube | Fibrobacteraceae | 0.377099 | 0.25939 | 0.074878 |
| 645 | Stomach Tube | Muribaculaceae | 0.369579 | 0.17473 | 0.050440 |
| 572 | Solid | Veillonellaceae | 0.368549 | 0.10245 | 0.029575 |
| 259 | Liquid Strained | Clostridiales_vadinBB60_group | 0.356928 | 0.09081 | 0.026215 |
| 102 | Feces | Spirochaetaceae | 0.347187 | 0.22783 | 0.065768 |
| 47 | Feces | F082 | 0.341935 | 0.12590 | 0.036343 |
| 681 | Stomach Tube | Succinivibrionaceae | 0.336053 | 0.27571 | 0.079590 |
| 595 | Stomach Tube | Burkholderiaceae | 0.331625 | 0.27181 | 0.078465 |
| 3 | Feces | Acidaminococcaceae | 0.319192 | 0.06945 | 0.020049 |
| 122 | Grab Sample | Anaeroplasmataceae | 0.307062 | 0.11445 | 0.033038 |
| 80 | Feces | Paludibacteraceae | 0.303656 | 0.13622 | 0.039325 |
| 266 | Liquid Strained | Desulfovibrionaceae | 0.299891 | 0.08871 | 0.025609 |
| 525 | Solid | Methanomethylophilaceae | 0.296907 | 0.08416 | 0.024296 |
| 653 | Stomach Tube | p-251-o5 | 0.296192 | 0.18872 | 0.054478 |
| 70 | Feces | Muribaculaceae | 0.291696 | 0.10340 | 0.029848 |
| 538 | Solid | p-251-o5 | 0.288969 | 0.09724 | 0.028071 |
| 415 | Liquid Unstrained | Muribaculaceae | 0.280209 | 0.11363 | 0.040174 |
| 374 | Liquid Unstrained | Clostridiales_vadinBB60_group | 0.258308 | 0.14999 | 0.053031 |
| 385 | Liquid Unstrained | Eggerthellaceae | 0.249293 | 0.09906 | 0.035025 |
| 271 | Liquid Strained | Elusimicrobiaceae | 0.247167 | 0.10371 | 0.029938 |
| 29 | Feces | Clostridiales_vadinBB60_group | 0.245353 | 0.15311 | 0.044200 |
| 410 | Liquid Unstrained | Methanomethylophilaceae | 0.243601 | 0.08607 | 0.030432 |
| 480 | Solid | Burkholderiaceae | 0.239162 | 0.24901 | 0.071882 |
| 128 | Grab Sample | Bacteroidales_RF16_group | 0.228827 | 0.07427 | 0.021439 |
| 566 | Solid | Succinivibrionaceae | 0.225922 | 0.16580 | 0.047861 |
| 335 | Liquid Strained | Streptococcaceae | 0.215900 | 0.10879 | 0.031406 |
| 135 | Grab Sample | Burkholderiaceae | 0.209240 | 0.10020 | 0.028926 |
| 295 | Liquid Strained | Methanomethylophilaceae | 0.208475 | 0.09661 | 0.027889 |
| 87 | Feces | Pirellulaceae | 0.206561 | 0.07625 | 0.022010 |
| 640 | Stomach Tube | Methanomethylophilaceae | 0.202565 | 0.07348 | 0.021210 |
| 113 | Feces | Victivallaceae | 0.198879 | 0.15588 | 0.044999 |
| 149 | Grab Sample | Defluviitaleaceae | 0.196038 | 0.08053 | 0.023248 |
| 40 | Feces | Eggerthellaceae | 0.189249 | 0.08373 | 0.024170 |
| 300 | Liquid Strained | Muribaculaceae | 0.181475 | 0.09106 | 0.026286 |
| 450 | Liquid Unstrained | Streptococcaceae | 0.179921 | 0.08149 | 0.028811 |
| 270 | Liquid Strained | Eggerthellaceae | 0.176277 | 0.08897 | 0.025683 |
| 200 | Grab Sample | Peptococcaceae | 0.175800 | 0.10497 | 0.030303 |
| 386 | Liquid Unstrained | Elusimicrobiaceae | 0.175441 | 0.11458 | 0.040510 |
| 387 | Liquid Unstrained | Endomicrobiaceae | 0.173038 | 0.12007 | 0.042452 |
| 180 | Grab Sample | Methanomethylophilaceae | 0.170696 | 0.06650 | 0.019196 |
| 545 | Solid | Peptococcaceae | 0.167197 | 0.05052 | 0.014583 |
| 609 | Stomach Tube | Defluviitaleaceae | 0.166117 | 0.06242 | 0.018019 |
| 467 | Solid | Anaeroplasmataceae | 0.162214 | 0.05784 | 0.016697 |
| 473 | Solid | Bacteroidales_RF16_group | 0.161196 | 0.07571 | 0.021855 |
| 272 | Liquid Strained | Endomicrobiaceae | 0.159378 | 0.14788 | 0.042690 |
| 494 | Solid | Defluviitaleaceae | 0.148982 | 0.04836 | 0.013962 |
| 604 | Stomach Tube | Clostridiales_vadinBB60_group | 0.143844 | 0.12588 | 0.036339 |
| 660 | Stomach Tube | Peptococcaceae | 0.143545 | 0.07142 | 0.020618 |
| 28 | Feces | Clostridiaceae_1 | 0.137297 | 0.06146 | 0.017742 |
| 617 | Stomach Tube | Endomicrobiaceae | 0.134121 | 0.12862 | 0.037130 |
| 662 | Stomach Tube | Pirellulaceae | 0.133296 | 0.04368 | 0.012609 |
| 502 | Solid | Endomicrobiaceae | 0.132840 | 0.07372 | 0.021281 |
| 565 | Solid | Streptococcaceae | 0.130788 | 0.16399 | 0.047341 |
| 19 | Feces | Bifidobacteriaceae | 0.128085 | 0.06899 | 0.019915 |
| 567 | Solid | Synergistaceae | 0.126694 | 0.03795 | 0.010956 |
| 177 | Grab Sample | Marinilabiliaceae | 0.122366 | 0.04732 | 0.013661 |
| 220 | Grab Sample | Streptococcaceae | 0.113880 | 0.08490 | 0.024509 |
| 379 | Liquid Unstrained | Defluviitaleaceae | 0.113587 | 0.04419 | 0.015625 |
| 475 | Solid | Bacteroidetes_BD2-2 | 0.110198 | 0.05620 | 0.016224 |
| 547 | Solid | Pirellulaceae | 0.107592 | 0.01948 | 0.005622 |
| 130 | Grab Sample | Bacteroidetes_BD2-2 | 0.106388 | 0.04375 | 0.012630 |
| 627 | Stomach Tube | Fusobacteriaceae | 0.105689 | 0.09255 | 0.026717 |
| 41 | Feces | Elusimicrobiaceae | 0.102092 | 0.05904 | 0.017042 |
| 202 | Grab Sample | Pirellulaceae | 0.101176 | 0.04403 | 0.012711 |
| 522 | Solid | Marinilabiliaceae | 0.097609 | 0.06302 | 0.018191 |
| 8 | Feces | Atopobiaceae | 0.095450 | 0.04035 | 0.011648 |
| 432 | Liquid Unstrained | Pirellulaceae | 0.094921 | 0.03686 | 0.013033 |
| 20 | Feces | Burkholderiaceae | 0.089456 | 0.04516 | 0.013035 |
| 430 | Liquid Unstrained | Peptococcaceae | 0.088746 | 0.07321 | 0.025885 |
| 157 | Grab Sample | Endomicrobiaceae | 0.088366 | 0.05187 | 0.014973 |
| 343 | Liquid Strained | Victivallaceae | 0.086966 | 0.04126 | 0.011909 |
| 222 | Grab Sample | Synergistaceae | 0.080729 | 0.05044 | 0.014561 |
| 407 | Liquid Unstrained | Marinilabiliaceae | 0.079882 | 0.04409 | 0.015587 |
| 428 | Liquid Unstrained | Pedosphaeraceae | 0.078697 | 0.03959 | 0.013997 |
| 637 | Stomach Tube | Marinilabiliaceae | 0.078628 | 0.07002 | 0.020213 |
| 16 | Feces | Barnesiellaceae | 0.076851 | 0.02568 | 0.007414 |
| 544 | Solid | PeH15 | 0.074235 | 0.02913 | 0.008409 |
| 313 | Liquid Strained | Pedosphaeraceae | 0.073596 | 0.06269 | 0.018096 |
| 34 | Feces | Defluviitaleaceae | 0.073182 | 0.03254 | 0.009394 |
| 64 | Feces | Methanocorpusculaceae | 0.072398 | 0.05968 | 0.017228 |
| 317 | Liquid Strained | Pirellulaceae | 0.072235 | 0.03548 | 0.010242 |
| 606 | Stomach Tube | Coriobacteriales_Incertae_Sedis | 0.071326 | 0.05090 | 0.014695 |
| 586 | Stomach Tube | Bacteroidaceae | 0.071087 | 0.11475 | 0.033127 |
| 226 | Grab Sample | vadinBE97 | 0.070891 | 0.04038 | 0.011656 |
| 287 | Liquid Strained | Lactobacillaceae | 0.069775 | 0.06637 | 0.019159 |
| 161 | Grab Sample | Eubacteriaceae | 0.068736 | 0.03572 | 0.010310 |
| 658 | Stomach Tube | Pedosphaeraceae | 0.067406 | 0.06005 | 0.017336 |
| 61 | Feces | Marinifilaceae | 0.066216 | 0.04162 | 0.012014 |
| 659 | Stomach Tube | PeH15 | 0.064715 | 0.03626 | 0.010466 |
| 458 | Liquid Unstrained | Victivallaceae | 0.064524 | 0.05513 | 0.019492 |
| 199 | Grab Sample | PeH15 | 0.063409 | 0.04192 | 0.012101 |
| 621 | Stomach Tube | Eubacteriaceae | 0.063345 | 0.03978 | 0.011483 |
| 78 | Feces | p-251-o5 | 0.062782 | 0.05180 | 0.014954 |
| 264 | Liquid Strained | Defluviitaleaceae | 0.062671 | 0.03757 | 0.010845 |
| 657 | Stomach Tube | Pasteurellaceae | 0.061972 | 0.06716 | 0.019389 |
| 311 | Liquid Strained | Paracaedibacteraceae | 0.061309 | 0.03007 | 0.008679 |
| 53 | Feces | GZKB124 | 0.060164 | 0.11122 | 0.032107 |
| 623 | Stomach Tube | Family_XI | 0.059822 | 0.06603 | 0.019060 |
| 321 | Liquid Strained | Pseudomonadaceae | 0.059767 | 0.06805 | 0.019645 |
| 529 | Solid | Moraxellaceae | 0.059274 | 0.16647 | 0.048055 |
| 506 | Solid | Eubacteriaceae | 0.059031 | 0.03127 | 0.009028 |
| 88 | Feces | Planococcaceae | 0.058235 | 0.07061 | 0.020384 |
| 402 | Liquid Unstrained | Lactobacillaceae | 0.058117 | 0.03608 | 0.012757 |
| 146 | Grab Sample | Coriobacteriales_Incertae_Sedis | 0.057232 | 0.02890 | 0.008343 |
| 491 | Solid | Coriobacteriales_Incertae_Sedis | 0.056256 | 0.02149 | 0.006204 |
| 292 | Liquid Strained | Marinilabiliaceae | 0.056163 | 0.04938 | 0.014256 |
| 682 | Stomach Tube | Synergistaceae | 0.056113 | 0.04641 | 0.013396 |
| 632 | Stomach Tube | Lactobacillaceae | 0.055846 | 0.04092 | 0.011811 |
| 315 | Liquid Strained | Peptococcaceae | 0.055806 | 0.03613 | 0.010430 |
| 543 | Solid | Pedosphaeraceae | 0.055375 | 0.03722 | 0.010745 |
| 571 | Solid | vadinBE97 | 0.053217 | 0.02680 | 0.007737 |
| 452 | Liquid Unstrained | Synergistaceae | 0.052819 | 0.02235 | 0.007901 |
| 492 | Solid | Corynebacteriaceae | 0.052490 | 0.10735 | 0.030990 |
| 111 | Feces | vadinBE97 | 0.052321 | 0.04605 | 0.013293 |
| 337 | Liquid Strained | Synergistaceae | 0.051608 | 0.03343 | 0.009650 |
| 426 | Liquid Unstrained | Paracaedibacteraceae | 0.051468 | 0.03729 | 0.013182 |
| 109 | Feces | Tannerellaceae | 0.051042 | 0.03069 | 0.008859 |
| 391 | Liquid Unstrained | Eubacteriaceae | 0.050990 | 0.03438 | 0.012154 |
| 356 | Liquid Unstrained | Bacteroidaceae | 0.049972 | 0.03979 | 0.014067 |
| 14 | Feces | Bacteroidales_UCG-001 | 0.048206 | 0.02883 | 0.008322 |
| 258 | Liquid Strained | Clostridiaceae_1 | 0.047419 | 0.03865 | 0.011159 |
| 429 | Liquid Unstrained | PeH15 | 0.046158 | 0.02941 | 0.010398 |
| 416 | Liquid Unstrained | Mycoplasmataceae | 0.045288 | 0.03608 | 0.012755 |
| 436 | Liquid Unstrained | Pseudomonadaceae | 0.045214 | 0.03532 | 0.012487 |
| 474 | Solid | Bacteroidales_UCG-001 | 0.044178 | 0.02459 | 0.007097 |
| 661 | Stomach Tube | Peptostreptococcaceae | 0.043530 | 0.01594 | 0.004601 |
| 152 | Grab Sample | Desulfuromonadaceae | 0.042774 | 0.02832 | 0.008176 |
| 597 | Stomach Tube | Cardiobacteriaceae | 0.042566 | 0.03387 | 0.009777 |
| 198 | Grab Sample | Pedosphaeraceae | 0.042548 | 0.03695 | 0.010668 |
| 541 | Solid | Paracaedibacteraceae | 0.040868 | 0.03335 | 0.009629 |
| 656 | Stomach Tube | Paracaedibacteraceae | 0.040550 | 0.02568 | 0.007413 |
| 590 | Stomach Tube | Bacteroidetes_BD2-2 | 0.039367 | 0.02317 | 0.006689 |
| 105 | Feces | Streptococcaceae | 0.039274 | 0.02798 | 0.008078 |
| 2 | Feces | Acetobacteraceae | 0.039145 | 0.03724 | 0.010751 |
| 21 | Feces | Campylobacteraceae | 0.038741 | 0.02917 | 0.008419 |
| 497 | Solid | Desulfuromonadaceae | 0.038547 | 0.02360 | 0.006813 |
| 688 | Stomach Tube | Victivallaceae | 0.038405 | 0.03573 | 0.010315 |
| 241 | Liquid Strained | Bacteroidaceae | 0.037620 | 0.03860 | 0.011143 |
| 323 | Liquid Strained | Rhizobiaceae | 0.037541 | 0.03476 | 0.010035 |
| 231 | Liquid Strained | 0319-6G20 | 0.037199 | 0.02142 | 0.006184 |
| 644 | Stomach Tube | Moraxellaceae | 0.037051 | 0.04045 | 0.011677 |
| 129 | Grab Sample | Bacteroidales_UCG-001 | 0.036976 | 0.02393 | 0.006907 |
| 316 | Liquid Strained | Peptostreptococcaceae | 0.036531 | 0.03227 | 0.009316 |
| 553 | Solid | Rhizobiaceae | 0.035823 | 0.03217 | 0.009286 |
| 360 | Liquid Unstrained | Bacteroidetes_BD2-2 | 0.035561 | 0.01890 | 0.006682 |
| 126 | Grab Sample | Bacteroidaceae | 0.035532 | 0.02987 | 0.008624 |
| 6 | Feces | Anaerolineaceae | 0.035167 | 0.01434 | 0.004140 |
| 589 | Stomach Tube | Bacteroidales_UCG-001 | 0.034726 | 0.03563 | 0.010285 |
| 346 | Liquid Unstrained | 0319-6G20 | 0.034156 | 0.03848 | 0.013604 |
| 382 | Liquid Unstrained | Desulfuromonadaceae | 0.033825 | 0.01931 | 0.006827 |
| 616 | Stomach Tube | Elusimicrobiaceae | 0.033798 | 0.02366 | 0.006829 |
| 642 | Stomach Tube | Microbacteriaceae | 0.032809 | 0.03284 | 0.009479 |
| 546 | Solid | Peptostreptococcaceae | 0.032794 | 0.02061 | 0.005950 |
| 431 | Liquid Unstrained | Peptostreptococcaceae | 0.032204 | 0.01756 | 0.006207 |
| 57 | Feces | Lactobacillaceae | 0.031440 | 0.02677 | 0.007727 |
| 359 | Liquid Unstrained | Bacteroidales_UCG-001 | 0.031398 | 0.02176 | 0.007693 |
| 668 | Stomach Tube | Rhizobiaceae | 0.030916 | 0.03065 | 0.008848 |
| 517 | Solid | Lactobacillaceae | 0.030634 | 0.02465 | 0.007115 |
| 633 | Stomach Tube | Leptotrichiaceae | 0.030396 | 0.05006 | 0.014450 |
| 245 | Liquid Strained | Bacteroidetes_BD2-2 | 0.030274 | 0.01563 | 0.004511 |
| 377 | Liquid Unstrained | Corynebacteriaceae | 0.029443 | 0.03101 | 0.010962 |
| 446 | Liquid Unstrained | Sphingomonadaceae | 0.029357 | 0.03590 | 0.012692 |
| 607 | Stomach Tube | Corynebacteriaceae | 0.029047 | 0.02805 | 0.008098 |
| 143 | Grab Sample | Clostridiaceae_1 | 0.027773 | 0.02463 | 0.007111 |
| 471 | Solid | Bacteroidaceae | 0.027522 | 0.02366 | 0.006831 |
| 201 | Grab Sample | Peptostreptococcaceae | 0.027319 | 0.01781 | 0.005141 |
| 666 | Stomach Tube | Pseudomonadaceae | 0.026882 | 0.03445 | 0.009944 |
| 244 | Liquid Strained | Bacteroidales_UCG-001 | 0.026616 | 0.02990 | 0.008630 |
| 156 | Grab Sample | Elusimicrobiaceae | 0.026613 | 0.02532 | 0.007308 |
| 647 | Stomach Tube | Neisseriaceae | 0.026201 | 0.03804 | 0.010980 |
| 176 | Grab Sample | Marinifilaceae | 0.025995 | 0.02105 | 0.006077 |
| 172 | Grab Sample | Lactobacillaceae | 0.025950 | 0.02155 | 0.006222 |
| 676 | Stomach Tube | Sphingomonadaceae | 0.025676 | 0.02909 | 0.008398 |
| 388 | Liquid Unstrained | Enterobacteriaceae | 0.025077 | 0.01960 | 0.006928 |
| 501 | Solid | Elusimicrobiaceae | 0.024949 | 0.01781 | 0.005143 |
| 144 | Grab Sample | Clostridiales_vadinBB60_group | 0.024787 | 0.02238 | 0.006461 |
| 373 | Liquid Unstrained | Clostridiaceae_1 | 0.024771 | 0.00887 | 0.003136 |
| 110 | Feces | Terasakiellaceae | 0.024248 | 0.02840 | 0.008198 |
| 561 | Solid | Sphingomonadaceae | 0.024161 | 0.02685 | 0.007751 |
| 331 | Liquid Strained | Sphingomonadaceae | 0.024039 | 0.03042 | 0.008781 |
| 618 | Stomach Tube | Enterobacteriaceae | 0.024030 | 0.02673 | 0.007718 |
| 437 | Liquid Unstrained | Puniceicoccaceae | 0.023500 | 0.02735 | 0.009669 |
| 376 | Liquid Unstrained | Coriobacteriales_Incertae_Sedis | 0.023124 | 0.01752 | 0.006196 |
| 520 | Solid | M2PB4-65_termite_group | 0.022957 | 0.01940 | 0.005599 |
| 251 | Liquid Strained | Campylobacteraceae | 0.022911 | 0.02738 | 0.007905 |
| 186 | Grab Sample | Mycoplasmataceae | 0.022419 | 0.02510 | 0.007247 |
| 46 | Feces | Eubacteriaceae | 0.022333 | 0.01495 | 0.004316 |
| 498 | Solid | Devosiaceae | 0.022316 | 0.01422 | 0.004105 |
| 612 | Stomach Tube | Desulfuromonadaceae | 0.022204 | 0.02251 | 0.006498 |
| 208 | Grab Sample | Rhizobiaceae | 0.022144 | 0.02111 | 0.006094 |
| 314 | Liquid Strained | PeH15 | 0.022031 | 0.02670 | 0.007707 |
| 649 | Stomach Tube | Nocardiaceae | 0.021847 | 0.01359 | 0.003923 |
| 488 | Solid | Clostridiaceae_1 | 0.021417 | 0.02079 | 0.006002 |
| 297 | Liquid Strained | Microbacteriaceae | 0.021216 | 0.02142 | 0.006184 |
| 301 | Liquid Strained | Mycoplasmataceae | 0.020624 | 0.02690 | 0.007766 |
| 196 | Grab Sample | Paracaedibacteraceae | 0.020053 | 0.01779 | 0.005135 |
| 380 | Liquid Unstrained | Desulfobulbaceae | 0.020019 | 0.02383 | 0.008426 |
| 655 | Stomach Tube | Paludibacteraceae | 0.020009 | 0.01491 | 0.004304 |
| 490 | Solid | COB_P4-1_termite_group | 0.019979 | 0.01485 | 0.004287 |
| 651 | Stomach Tube | Oligoflexaceae | 0.019945 | 0.02065 | 0.005960 |
| 153 | Grab Sample | Devosiaceae | 0.019573 | 0.01757 | 0.005071 |
| 262 | Liquid Strained | Corynebacteriaceae | 0.019564 | 0.02327 | 0.006717 |
| 265 | Liquid Strained | Desulfobulbaceae | 0.019531 | 0.01404 | 0.004054 |
| 521 | Solid | Marinifilaceae | 0.019393 | 0.01509 | 0.004357 |
| 322 | Liquid Strained | Puniceicoccaceae | 0.019346 | 0.02347 | 0.006774 |
| 527 | Solid | Microbacteriaceae | 0.019278 | 0.01399 | 0.004039 |
| 414 | Liquid Unstrained | Moraxellaceae | 0.019234 | 0.02319 | 0.008201 |
| 508 | Solid | Family_XI | 0.019088 | 0.03173 | 0.009160 |
| 664 | Stomach Tube | Porphyromonadaceae | 0.018788 | 0.02410 | 0.006958 |
| 50 | Feces | Fibrobacteraceae | 0.018699 | 0.01805 | 0.005210 |
| 603 | Stomach Tube | Clostridiaceae_1 | 0.018597 | 0.01059 | 0.003057 |
| 596 | Stomach Tube | Campylobacteraceae | 0.018162 | 0.02628 | 0.007585 |
| 216 | Grab Sample | Sphingomonadaceae | 0.017641 | 0.01910 | 0.005513 |
| 584 | Stomach Tube | Bacillaceae | 0.016902 | 0.02553 | 0.007370 |
| 406 | Liquid Unstrained | Marinifilaceae | 0.016459 | 0.01805 | 0.006380 |
| 145 | Grab Sample | COB_P4-1_termite_group | 0.016232 | 0.02194 | 0.006333 |
| 289 | Liquid Strained | Leuconostocaceae | 0.016175 | 0.02517 | 0.007266 |
| 425 | Liquid Unstrained | Paludibacteraceae | 0.016139 | 0.01815 | 0.006415 |
| 646 | Stomach Tube | Mycoplasmataceae | 0.016099 | 0.01811 | 0.005228 |
| 568 | Solid | Syntrophomonadaceae | 0.015737 | 0.00967 | 0.002791 |
| 610 | Stomach Tube | Desulfobulbaceae | 0.015682 | 0.01561 | 0.004505 |
| 531 | Solid | Mycoplasmataceae | 0.015630 | 0.02135 | 0.006162 |
| 158 | Grab Sample | Enterobacteriaceae | 0.015240 | 0.02024 | 0.005844 |
| 663 | Stomach Tube | Planococcaceae | 0.015003 | 0.01817 | 0.005244 |
| 147 | Grab Sample | Corynebacteriaceae | 0.014852 | 0.01934 | 0.005584 |
| 672 | Stomach Tube | Saccharimonadaceae | 0.014464 | 0.01235 | 0.003564 |
| 350 | Liquid Unstrained | Akkermansiaceae | 0.014429 | 0.01506 | 0.005323 |
| 675 | Stomach Tube | Sphingobacteriaceae | 0.014413 | 0.01673 | 0.004829 |
| 330 | Liquid Strained | Sphingobacteriaceae | 0.014247 | 0.01833 | 0.005290 |
| 182 | Grab Sample | Microbacteriaceae | 0.014190 | 0.01921 | 0.005545 |
| 613 | Stomach Tube | Devosiaceae | 0.014048 | 0.01362 | 0.003931 |
| 540 | Solid | Paludibacteraceae | 0.013924 | 0.01456 | 0.004203 |
| 412 | Liquid Unstrained | Microbacteriaceae | 0.013779 | 0.01436 | 0.005077 |
| 445 | Liquid Unstrained | Sphingobacteriaceae | 0.013391 | 0.02110 | 0.007460 |
| 273 | Liquid Strained | Enterobacteriaceae | 0.013357 | 0.01312 | 0.003789 |
| 7 | Feces | Anaeroplasmataceae | 0.013311 | 0.01168 | 0.003371 |
| 299 | Liquid Strained | Moraxellaceae | 0.013064 | 0.01234 | 0.003563 |
| 175 | Grab Sample | M2PB4-65_termite_group | 0.013056 | 0.01620 | 0.004676 |
| 163 | Grab Sample | Family_XI | 0.012993 | 0.02246 | 0.006483 |
| 345 | Liquid Strained | Xanthomonadaceae | 0.012979 | 0.01750 | 0.005051 |
| 278 | Liquid Strained | Family_XI | 0.012832 | 0.01923 | 0.005552 |
| 291 | Liquid Strained | Marinifilaceae | 0.012604 | 0.01120 | 0.003233 |
| 393 | Liquid Unstrained | Family_XI | 0.012370 | 0.02313 | 0.008177 |
| 267 | Liquid Strained | Desulfuromonadaceae | 0.012357 | 0.01448 | 0.004181 |
| 195 | Grab Sample | Paludibacteraceae | 0.012100 | 0.01156 | 0.003336 |
| 438 | Liquid Unstrained | Rhizobiaceae | 0.011973 | 0.01288 | 0.004553 |
| 465 | Solid | Akkermansiaceae | 0.011909 | 0.00862 | 0.002487 |
| 503 | Solid | Enterobacteriaceae | 0.011871 | 0.01258 | 0.003631 |
| 261 | Liquid Strained | Coriobacteriales_Incertae_Sedis | 0.011861 | 0.01745 | 0.005038 |
| 504 | Solid | Enterococcaceae | 0.011840 | 0.01326 | 0.003828 |
| 554 | Solid | Rhodobacteraceae | 0.011757 | 0.03730 | 0.010766 |
| 375 | Liquid Unstrained | COB_P4-1_termite_group | 0.011549 | 0.02044 | 0.007225 |
| 576 | Stomach Tube | 0319-6G20 | 0.011458 | 0.01144 | 0.003302 |
| 215 | Grab Sample | Sphingobacteriaceae | 0.011142 | 0.01291 | 0.003728 |
| 690 | Stomach Tube | Xanthomonadaceae | 0.011051 | 0.01697 | 0.004898 |
| 235 | Liquid Strained | Akkermansiaceae | 0.010743 | 0.02096 | 0.006049 |
| 268 | Liquid Strained | Devosiaceae | 0.010652 | 0.01544 | 0.004458 |
| 223 | Grab Sample | Syntrophomonadaceae | 0.010589 | 0.01446 | 0.004173 |
| 634 | Stomach Tube | Leuconostocaceae | 0.010566 | 0.01540 | 0.004446 |
| 206 | Grab Sample | Pseudomonadaceae | 0.010421 | 0.01179 | 0.003403 |
| 667 | Stomach Tube | Puniceicoccaceae | 0.010249 | 0.02161 | 0.006239 |
| 228 | Grab Sample | Victivallaceae | 0.010203 | 0.01729 | 0.004990 |
| 605 | Stomach Tube | COB_P4-1_termite_group | 0.010136 | 0.01922 | 0.005548 |
| 81 | Feces | Paracaedibacteraceae | 0.010107 | 0.01009 | 0.002914 |
| 389 | Liquid Unstrained | Enterococcaceae | 0.009852 | 0.01506 | 0.005324 |
| 139 | Grab Sample | Caulobacteraceae | 0.009847 | 0.01328 | 0.003834 |
| 310 | Liquid Strained | Paludibacteraceae | 0.009671 | 0.01383 | 0.003994 |
| 274 | Liquid Strained | Enterococcaceae | 0.009554 | 0.01604 | 0.004630 |
| 552 | Solid | Puniceicoccaceae | 0.009533 | 0.01480 | 0.004272 |
| 191 | Grab Sample | Oligoflexaceae | 0.009434 | 0.01077 | 0.003110 |
| 306 | Liquid Strained | Oligoflexaceae | 0.009407 | 0.01333 | 0.003848 |
| 212 | Grab Sample | Saccharimonadaceae | 0.009296 | 0.01492 | 0.004306 |
| 324 | Liquid Strained | Rhodobacteraceae | 0.009238 | 0.01977 | 0.005706 |
| 421 | Liquid Unstrained | Oligoflexaceae | 0.009093 | 0.01400 | 0.004949 |
| 679 | Stomach Tube | Staphylococcaceae | 0.008935 | 0.01114 | 0.003215 |
| 413 | Liquid Unstrained | Micrococcaceae | 0.008915 | 0.00833 | 0.002947 |
| 460 | Liquid Unstrained | Xanthomonadaceae | 0.008705 | 0.01069 | 0.003781 |
| 31 | Feces | Coriobacteriales_Incertae_Sedis | 0.008646 | 0.01039 | 0.003000 |
| 92 | Feces | Puniceicoccaceae | 0.008564 | 0.01106 | 0.003192 |
| 93 | Feces | Rhizobiaceae | 0.008527 | 0.01238 | 0.003574 |
| 189 | Grab Sample | Nocardiaceae | 0.008524 | 0.01372 | 0.003960 |
| 433 | Liquid Unstrained | Planococcaceae | 0.008516 | 0.00977 | 0.003454 |
| 580 | Stomach Tube | Akkermansiaceae | 0.008449 | 0.01822 | 0.005260 |
| 551 | Solid | Pseudomonadaceae | 0.008411 | 0.01293 | 0.003731 |
| 439 | Liquid Unstrained | Rhodobacteraceae | 0.008172 | 0.02311 | 0.008172 |
| 224 | Grab Sample | Tannerellaceae | 0.008100 | 0.01354 | 0.003910 |
| 684 | Stomach Tube | Tannerellaceae | 0.008024 | 0.01124 | 0.003245 |
| 442 | Liquid Unstrained | Saccharimonadaceae | 0.007933 | 0.01167 | 0.004128 |
| 489 | Solid | Clostridiales_vadinBB60_group | 0.007843 | 0.01064 | 0.003071 |
| 536 | Solid | Oligoflexaceae | 0.007744 | 0.01022 | 0.002951 |
| 276 | Liquid Strained | Eubacteriaceae | 0.007682 | 0.00900 | 0.002599 |
| 519 | Solid | Leuconostocaceae | 0.007665 | 0.01402 | 0.004047 |
| 367 | Liquid Unstrained | Cardiobacteriaceae | 0.007579 | 0.01131 | 0.004000 |
| 43 | Feces | Enterobacteriaceae | 0.007410 | 0.01018 | 0.002940 |
| 636 | Stomach Tube | Marinifilaceae | 0.007326 | 0.01163 | 0.003356 |
| 569 | Solid | Tannerellaceae | 0.007273 | 0.00958 | 0.002766 |
| 643 | Stomach Tube | Micrococcaceae | 0.007272 | 0.01320 | 0.003809 |
| 495 | Solid | Desulfobulbaceae | 0.007171 | 0.00908 | 0.002621 |
| 364 | Liquid Unstrained | Bifidobacteriaceae | 0.007158 | 0.00831 | 0.002938 |
| 106 | Feces | Succinivibrionaceae | 0.007032 | 0.01058 | 0.003054 |
| 137 | Grab Sample | Cardiobacteriaceae | 0.006916 | 0.01109 | 0.003202 |
| 579 | Stomach Tube | Aerococcaceae | 0.006833 | 0.01062 | 0.003066 |
| 481 | Solid | Campylobacteraceae | 0.006831 | 0.00938 | 0.002708 |
| 560 | Solid | Sphingobacteriaceae | 0.006648 | 0.00984 | 0.002841 |
| 230 | Grab Sample | Xanthomonadaceae | 0.006581 | 0.01284 | 0.003705 |
| 683 | Stomach Tube | Syntrophomonadaceae | 0.006567 | 0.01018 | 0.002939 |
| 120 | Grab Sample | Akkermansiaceae | 0.006546 | 0.01421 | 0.004101 |
| 366 | Liquid Unstrained | Campylobacteraceae | 0.006356 | 0.00957 | 0.003384 |
| 73 | Feces | Nitrosomonadaceae | 0.006290 | 0.01090 | 0.003147 |
| 383 | Liquid Unstrained | Devosiaceae | 0.006279 | 0.00893 | 0.003156 |
| 673 | Stomach Tube | Sanguibacteraceae | 0.006265 | 0.00960 | 0.002771 |
| 116 | Grab Sample | 0319-6G20 | 0.006238 | 0.00950 | 0.002741 |
| 454 | Liquid Unstrained | Tannerellaceae | 0.006024 | 0.00927 | 0.003277 |
| 174 | Grab Sample | Leuconostocaceae | 0.006018 | 0.00931 | 0.002688 |
| 150 | Grab Sample | Desulfobulbaceae | 0.005998 | 0.00894 | 0.002582 |
| 282 | Liquid Strained | Fusobacteriaceae | 0.005850 | 0.00960 | 0.002771 |
| 573 | Solid | Victivallaceae | 0.005835 | 0.00943 | 0.002721 |
| 598 | Stomach Tube | Carnobacteriaceae | 0.005834 | 0.01105 | 0.003190 |
| 564 | Solid | Staphylococcaceae | 0.005711 | 0.00915 | 0.002642 |
| 312 | Liquid Strained | Pasteurellaceae | 0.005474 | 0.00828 | 0.002390 |
| 405 | Liquid Unstrained | M2PB4-65_termite_group | 0.005428 | 0.00770 | 0.002722 |
| 397 | Liquid Unstrained | Fusobacteriaceae | 0.005345 | 0.01225 | 0.004331 |
| 558 | Solid | Sanguibacteraceae | 0.005328 | 0.01039 | 0.003000 |
| 260 | Liquid Strained | COB_P4-1_termite_group | 0.005313 | 0.01142 | 0.003296 |
| 362 | Liquid Unstrained | Beijerinckiaceae | 0.005180 | 0.00800 | 0.002830 |
| 534 | Solid | Nocardiaceae | 0.005171 | 0.00857 | 0.002473 |
| 294 | Liquid Strained | Methanocorpusculaceae | 0.005139 | 0.00789 | 0.002277 |
| 417 | Liquid Unstrained | Neisseriaceae | 0.004997 | 0.00765 | 0.002704 |
| 419 | Liquid Unstrained | Nocardiaceae | 0.004994 | 0.00961 | 0.003397 |
| 339 | Liquid Strained | Tannerellaceae | 0.004955 | 0.01071 | 0.003093 |
| 484 | Solid | Caulobacteraceae | 0.004837 | 0.00800 | 0.002310 |
| 639 | Stomach Tube | Methanocorpusculaceae | 0.004764 | 0.00910 | 0.002626 |
| 247 | Liquid Strained | Beijerinckiaceae | 0.004646 | 0.00716 | 0.002066 |
| 12 | Feces | Bacteroidales_BS11_gut_group | 0.004608 | 0.00728 | 0.002101 |
| 327 | Liquid Strained | Saccharimonadaceae | 0.004565 | 0.00970 | 0.002799 |
| 453 | Liquid Unstrained | Syntrophomonadaceae | 0.004527 | 0.00854 | 0.003018 |
| 619 | Stomach Tube | Enterococcaceae | 0.004474 | 0.00879 | 0.002538 |
| 427 | Liquid Unstrained | Pasteurellaceae | 0.004470 | 0.00619 | 0.002188 |
| 499 | Solid | Dysgonomonadaceae | 0.004465 | 0.01358 | 0.003919 |
| 184 | Grab Sample | Moraxellaceae | 0.004450 | 0.01144 | 0.003302 |
| 443 | Liquid Unstrained | Sanguibacteraceae | 0.004430 | 0.00832 | 0.002943 |
| 65 | Feces | Methanomethylophilaceae | 0.004428 | 0.00972 | 0.002806 |
| 197 | Grab Sample | Pasteurellaceae | 0.004255 | 0.00774 | 0.002233 |
| 209 | Grab Sample | Rhodobacteraceae | 0.004225 | 0.00780 | 0.002252 |
| 207 | Grab Sample | Puniceicoccaceae | 0.004219 | 0.00768 | 0.002218 |
| 599 | Stomach Tube | Caulobacteraceae | 0.004160 | 0.00807 | 0.002330 |
| 479 | Solid | Bifidobacteriaceae | 0.004095 | 0.00831 | 0.002398 |
| 384 | Liquid Unstrained | Dysgonomonadaceae | 0.004086 | 0.01156 | 0.004086 |
| 44 | Feces | Enterococcaceae | 0.004080 | 0.00671 | 0.001937 |
| 592 | Stomach Tube | Beijerinckiaceae | 0.003940 | 0.00739 | 0.002133 |
| 461 | Solid | 0319-6G20 | 0.003940 | 0.00608 | 0.001755 |
| 159 | Grab Sample | Enterococcaceae | 0.003925 | 0.00723 | 0.002086 |
| 470 | Solid | Bacteriovoracaceae | 0.003837 | 0.00739 | 0.002132 |
| 557 | Solid | Saccharimonadaceae | 0.003777 | 0.00745 | 0.002152 |
| 449 | Liquid Unstrained | Staphylococcaceae | 0.003708 | 0.00781 | 0.002761 |
| 252 | Liquid Strained | Cardiobacteriaceae | 0.003585 | 0.00582 | 0.001680 |
| 404 | Liquid Unstrained | Leuconostocaceae | 0.003440 | 0.00641 | 0.002266 |
| 302 | Liquid Strained | Neisseriaceae | 0.003374 | 0.00613 | 0.001770 |
| 249 | Liquid Strained | Bifidobacteriaceae | 0.003305 | 0.00617 | 0.001781 |
| 67 | Feces | Microbacteriaceae | 0.003283 | 0.00643 | 0.001855 |
| 32 | Feces | Corynebacteriaceae | 0.003280 | 0.00491 | 0.001417 |
| 512 | Solid | Fusobacteriaceae | 0.003275 | 0.00490 | 0.001414 |
| 112 | Feces | Veillonellaceae | 0.003185 | 0.00592 | 0.001708 |
| 338 | Liquid Strained | Syntrophomonadaceae | 0.003165 | 0.00821 | 0.002370 |
| 239 | Liquid Strained | Bacillaceae | 0.003149 | 0.00771 | 0.002227 |
| 136 | Grab Sample | Campylobacteraceae | 0.003135 | 0.00778 | 0.002246 |
| 524 | Solid | Methanocorpusculaceae | 0.003118 | 0.00475 | 0.001372 |
| 635 | Stomach Tube | M2PB4-65_termite_group | 0.003070 | 0.00769 | 0.002219 |
| 234 | Liquid Strained | Aerococcaceae | 0.003042 | 0.00810 | 0.002338 |
| 298 | Liquid Strained | Micrococcaceae | 0.003002 | 0.00797 | 0.002300 |
| 218 | Grab Sample | Spirosomaceae | 0.002993 | 0.00702 | 0.002026 |
| 409 | Liquid Unstrained | Methanocorpusculaceae | 0.002976 | 0.00577 | 0.002039 |
| 213 | Grab Sample | Sanguibacteraceae | 0.002882 | 0.00678 | 0.001956 |
| 340 | Liquid Strained | Terasakiellaceae | 0.002859 | 0.00857 | 0.002473 |
| 125 | Grab Sample | Bacteriovoracaceae | 0.002827 | 0.00666 | 0.001921 |
| 17 | Feces | Beijerinckiaceae | 0.002809 | 0.00542 | 0.001564 |
| 594 | Stomach Tube | Bifidobacteriaceae | 0.002795 | 0.00507 | 0.001463 |
| 318 | Liquid Strained | Planococcaceae | 0.002769 | 0.00658 | 0.001901 |
| 334 | Liquid Strained | Staphylococcaceae | 0.002763 | 0.00649 | 0.001874 |
| 52 | Feces | Fusobacteriaceae | 0.002757 | 0.00500 | 0.001443 |
| 203 | Grab Sample | Planococcaceae | 0.002692 | 0.00932 | 0.002692 |
| 97 | Feces | Saccharimonadaceae | 0.002640 | 0.00482 | 0.001393 |
| 477 | Solid | Beijerinckiaceae | 0.002619 | 0.00478 | 0.001381 |
| 478 | Solid | Beutenbergiaceae | 0.002500 | 0.00689 | 0.001989 |
| 253 | Liquid Strained | Carnobacteriaceae | 0.002454 | 0.00850 | 0.002454 |
| 288 | Liquid Strained | Leptotrichiaceae | 0.002454 | 0.00850 | 0.002454 |
| 434 | Liquid Unstrained | Porphyromonadaceae | 0.002452 | 0.00458 | 0.001618 |
| 548 | Solid | Planococcaceae | 0.002440 | 0.00622 | 0.001795 |
| 132 | Grab Sample | Beijerinckiaceae | 0.002372 | 0.00558 | 0.001611 |
| 240 | Liquid Strained | Bacteriovoracaceae | 0.002319 | 0.00547 | 0.001578 |
| 448 | Liquid Unstrained | Spirosomaceae | 0.001968 | 0.00557 | 0.001968 |
| 33 | Feces | Deferribacteraceae | 0.001954 | 0.00677 | 0.001954 |
| 100 | Feces | Sphingobacteriaceae | 0.001954 | 0.00677 | 0.001954 |
| 549 | Solid | Porphyromonadaceae | 0.001854 | 0.00477 | 0.001378 |
| 539 | Solid | p-2534-18B5_gut_group | 0.001850 | 0.00432 | 0.001248 |
| 514 | Solid | Hymenobacteraceae | 0.001800 | 0.00421 | 0.001215 |
| 575 | Solid | Xanthomonadaceae | 0.001800 | 0.00421 | 0.001215 |
| 255 | Liquid Strained | Cellvibrionaceae | 0.001620 | 0.00437 | 0.001263 |
| 119 | Grab Sample | Aerococcaceae | 0.001591 | 0.00551 | 0.001591 |
| 167 | Grab Sample | Fusobacteriaceae | 0.001591 | 0.00551 | 0.001591 |
| 528 | Solid | Micrococcaceae | 0.001587 | 0.00372 | 0.001074 |
| 124 | Grab Sample | Bacillaceae | 0.001579 | 0.00547 | 0.001579 |
| 173 | Grab Sample | Leptotrichiaceae | 0.001579 | 0.00547 | 0.001579 |
| 179 | Grab Sample | Methanocorpusculaceae | 0.001579 | 0.00547 | 0.001579 |
| 399 | Liquid Unstrained | Hymenobacteraceae | 0.001554 | 0.00440 | 0.001554 |
| 455 | Liquid Unstrained | Terasakiellaceae | 0.001554 | 0.00440 | 0.001554 |
| 459 | Liquid Unstrained | Weeksellaceae | 0.001554 | 0.00440 | 0.001554 |
| 482 | Solid | Cardiobacteriaceae | 0.001517 | 0.00372 | 0.001075 |
| 333 | Liquid Strained | Spirosomaceae | 0.001507 | 0.00522 | 0.001507 |
| 305 | Liquid Strained | Nocardioidaceae | 0.001501 | 0.00398 | 0.001150 |
| 104 | Feces | Staphylococcaceae | 0.001454 | 0.00504 | 0.001454 |
| 483 | Solid | Carnobacteriaceae | 0.001437 | 0.00348 | 0.001006 |
| 74 | Feces | Nocardiaceae | 0.001411 | 0.00330 | 0.000952 |
| 254 | Liquid Strained | Caulobacteraceae | 0.001395 | 0.00364 | 0.001051 |
| 304 | Liquid Strained | Nocardiaceae | 0.001395 | 0.00364 | 0.001051 |
| 77 | Feces | Oligosphaeraceae | 0.001367 | 0.00474 | 0.001367 |
| 26 | Feces | Chitinophagaceae | 0.001357 | 0.00470 | 0.001357 |
| 101 | Feces | Sphingomonadaceae | 0.001357 | 0.00470 | 0.001357 |
| 190 | Grab Sample | Nocardioidaceae | 0.001291 | 0.00447 | 0.001291 |
| 600 | Stomach Tube | Cellvibrionaceae | 0.001285 | 0.00445 | 0.001285 |
| 650 | Stomach Tube | Nocardioidaceae | 0.001285 | 0.00445 | 0.001285 |
| 290 | Liquid Strained | M2PB4-65_termite_group | 0.001239 | 0.00429 | 0.001239 |
| 328 | Liquid Strained | Sanguibacteraceae | 0.001239 | 0.00429 | 0.001239 |
| 593 | Stomach Tube | Beutenbergiaceae | 0.001196 | 0.00414 | 0.001196 |
| 396 | Liquid Unstrained | Flavobacteriaceae | 0.001090 | 0.00308 | 0.001090 |
| 400 | Liquid Unstrained | Kineosporiaceae | 0.001090 | 0.00308 | 0.001090 |
| 133 | Grab Sample | Beutenbergiaceae | 0.001054 | 0.00365 | 0.001054 |
| 138 | Grab Sample | Carnobacteriaceae | 0.001054 | 0.00365 | 0.001054 |
| 204 | Grab Sample | Porphyromonadaceae | 0.001054 | 0.00365 | 0.001054 |
| 219 | Grab Sample | Staphylococcaceae | 0.001054 | 0.00365 | 0.001054 |
| 296 | Liquid Strained | Methanosarcinaceae | 0.001015 | 0.00351 | 0.001015 |
| 319 | Liquid Strained | Porphyromonadaceae | 0.001015 | 0.00351 | 0.001015 |
| 674 | Stomach Tube | Solirubrobacteraceae | 0.000993 | 0.00344 | 0.000993 |
| 349 | Liquid Unstrained | Aerococcaceae | 0.000984 | 0.00278 | 0.000984 |
| 369 | Liquid Unstrained | Caulobacteraceae | 0.000984 | 0.00278 | 0.000984 |
| 370 | Liquid Unstrained | Cellvibrionaceae | 0.000984 | 0.00278 | 0.000984 |
| 48 | Feces | Family_XI | 0.000977 | 0.00339 | 0.000977 |
| 42 | Feces | Endomicrobiaceae | 0.000968 | 0.00335 | 0.000968 |
| 98 | Feces | Sanguibacteraceae | 0.000945 | 0.00327 | 0.000945 |
| 91 | Feces | Pseudomonadaceae | 0.000930 | 0.00322 | 0.000930 |
| 115 | Feces | Xanthomonadaceae | 0.000930 | 0.00322 | 0.000930 |
| 486 | Solid | Chitinophagaceae | 0.000853 | 0.00296 | 0.000853 |
| 9 | Feces | Bacillaceae | 0.000844 | 0.00292 | 0.000844 |
| 68 | Feces | Micrococcaceae | 0.000844 | 0.00292 | 0.000844 |
| 72 | Feces | Neisseriaceae | 0.000844 | 0.00292 | 0.000844 |
| 82 | Feces | Pasteurellaceae | 0.000844 | 0.00292 | 0.000844 |
| 464 | Solid | Aerococcaceae | 0.000826 | 0.00286 | 0.000826 |
| 469 | Solid | Bacillaceae | 0.000826 | 0.00286 | 0.000826 |
| 526 | Solid | Methanosarcinaceae | 0.000826 | 0.00286 | 0.000826 |
| 284 | Liquid Strained | Hymenobacteraceae | 0.000762 | 0.00264 | 0.000762 |
| 309 | Liquid Strained | p-2534-18B5_gut_group | 0.000762 | 0.00264 | 0.000762 |
| 38 | Feces | Devosiaceae | 0.000727 | 0.00252 | 0.000727 |
| 107 | Feces | Synergistaceae | 0.000727 | 0.00252 | 0.000727 |
| 54 | Feces | Hymenobacteraceae | 0.000684 | 0.00237 | 0.000684 |
| 62 | Feces | Marinilabiliaceae | 0.000684 | 0.00237 | 0.000684 |
| 76 | Feces | Oligoflexaceae | 0.000684 | 0.00237 | 0.000684 |
| 570 | Solid | Terasakiellaceae | 0.000650 | 0.00225 | 0.000650 |
| 542 | Solid | Pasteurellaceae | 0.000534 | 0.00185 | 0.000534 |
| 563 | Solid | Spirosomaceae | 0.000534 | 0.00185 | 0.000534 |
| 1 | Feces | 0319-6G20 | 0.000000 | 0.00000 | 0.000000 |
| 4 | Feces | Aerococcaceae | 0.000000 | 0.00000 | 0.000000 |
| 10 | Feces | Bacteriovoracaceae | 0.000000 | 0.00000 | 0.000000 |
| 15 | Feces | Bacteroidetes_BD2-2 | 0.000000 | 0.00000 | 0.000000 |
| 18 | Feces | Beutenbergiaceae | 0.000000 | 0.00000 | 0.000000 |
| 22 | Feces | Cardiobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 23 | Feces | Carnobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 24 | Feces | Caulobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 25 | Feces | Cellvibrionaceae | 0.000000 | 0.00000 | 0.000000 |
| 30 | Feces | COB_P4-1_termite_group | 0.000000 | 0.00000 | 0.000000 |
| 35 | Feces | Desulfobulbaceae | 0.000000 | 0.00000 | 0.000000 |
| 37 | Feces | Desulfuromonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 39 | Feces | Dysgonomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 51 | Feces | Flavobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 55 | Feces | Kineosporiaceae | 0.000000 | 0.00000 | 0.000000 |
| 58 | Feces | Leptotrichiaceae | 0.000000 | 0.00000 | 0.000000 |
| 59 | Feces | Leuconostocaceae | 0.000000 | 0.00000 | 0.000000 |
| 60 | Feces | M2PB4-65_termite_group | 0.000000 | 0.00000 | 0.000000 |
| 66 | Feces | Methanosarcinaceae | 0.000000 | 0.00000 | 0.000000 |
| 69 | Feces | Moraxellaceae | 0.000000 | 0.00000 | 0.000000 |
| 71 | Feces | Mycoplasmataceae | 0.000000 | 0.00000 | 0.000000 |
| 75 | Feces | Nocardioidaceae | 0.000000 | 0.00000 | 0.000000 |
| 83 | Feces | Pedosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 84 | Feces | PeH15 | 0.000000 | 0.00000 | 0.000000 |
| 89 | Feces | Porphyromonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 94 | Feces | Rhodobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 99 | Feces | Solirubrobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 103 | Feces | Spirosomaceae | 0.000000 | 0.00000 | 0.000000 |
| 108 | Feces | Syntrophomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 114 | Feces | Weeksellaceae | 0.000000 | 0.00000 | 0.000000 |
| 117 | Grab Sample | Acetobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 131 | Grab Sample | Barnesiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 134 | Grab Sample | Bifidobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 140 | Grab Sample | Cellvibrionaceae | 0.000000 | 0.00000 | 0.000000 |
| 141 | Grab Sample | Chitinophagaceae | 0.000000 | 0.00000 | 0.000000 |
| 148 | Grab Sample | Deferribacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 154 | Grab Sample | Dysgonomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 166 | Grab Sample | Flavobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 168 | Grab Sample | GZKB124 | 0.000000 | 0.00000 | 0.000000 |
| 169 | Grab Sample | Hymenobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 170 | Grab Sample | Kineosporiaceae | 0.000000 | 0.00000 | 0.000000 |
| 181 | Grab Sample | Methanosarcinaceae | 0.000000 | 0.00000 | 0.000000 |
| 183 | Grab Sample | Micrococcaceae | 0.000000 | 0.00000 | 0.000000 |
| 187 | Grab Sample | Neisseriaceae | 0.000000 | 0.00000 | 0.000000 |
| 188 | Grab Sample | Nitrosomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 192 | Grab Sample | Oligosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 194 | Grab Sample | p-2534-18B5_gut_group | 0.000000 | 0.00000 | 0.000000 |
| 214 | Grab Sample | Solirubrobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 225 | Grab Sample | Terasakiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 229 | Grab Sample | Weeksellaceae | 0.000000 | 0.00000 | 0.000000 |
| 232 | Liquid Strained | Acetobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 246 | Liquid Strained | Barnesiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 248 | Liquid Strained | Beutenbergiaceae | 0.000000 | 0.00000 | 0.000000 |
| 256 | Liquid Strained | Chitinophagaceae | 0.000000 | 0.00000 | 0.000000 |
| 263 | Liquid Strained | Deferribacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 269 | Liquid Strained | Dysgonomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 281 | Liquid Strained | Flavobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 283 | Liquid Strained | GZKB124 | 0.000000 | 0.00000 | 0.000000 |
| 285 | Liquid Strained | Kineosporiaceae | 0.000000 | 0.00000 | 0.000000 |
| 303 | Liquid Strained | Nitrosomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 307 | Liquid Strained | Oligosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 329 | Liquid Strained | Solirubrobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 344 | Liquid Strained | Weeksellaceae | 0.000000 | 0.00000 | 0.000000 |
| 347 | Liquid Unstrained | Acetobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 354 | Liquid Unstrained | Bacillaceae | 0.000000 | 0.00000 | 0.000000 |
| 355 | Liquid Unstrained | Bacteriovoracaceae | 0.000000 | 0.00000 | 0.000000 |
| 361 | Liquid Unstrained | Barnesiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 363 | Liquid Unstrained | Beutenbergiaceae | 0.000000 | 0.00000 | 0.000000 |
| 368 | Liquid Unstrained | Carnobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 371 | Liquid Unstrained | Chitinophagaceae | 0.000000 | 0.00000 | 0.000000 |
| 378 | Liquid Unstrained | Deferribacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 398 | Liquid Unstrained | GZKB124 | 0.000000 | 0.00000 | 0.000000 |
| 403 | Liquid Unstrained | Leptotrichiaceae | 0.000000 | 0.00000 | 0.000000 |
| 411 | Liquid Unstrained | Methanosarcinaceae | 0.000000 | 0.00000 | 0.000000 |
| 418 | Liquid Unstrained | Nitrosomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 420 | Liquid Unstrained | Nocardioidaceae | 0.000000 | 0.00000 | 0.000000 |
| 422 | Liquid Unstrained | Oligosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 424 | Liquid Unstrained | p-2534-18B5_gut_group | 0.000000 | 0.00000 | 0.000000 |
| 444 | Liquid Unstrained | Solirubrobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 462 | Solid | Acetobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 476 | Solid | Barnesiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 485 | Solid | Cellvibrionaceae | 0.000000 | 0.00000 | 0.000000 |
| 493 | Solid | Deferribacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 511 | Solid | Flavobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 513 | Solid | GZKB124 | 0.000000 | 0.00000 | 0.000000 |
| 515 | Solid | Kineosporiaceae | 0.000000 | 0.00000 | 0.000000 |
| 518 | Solid | Leptotrichiaceae | 0.000000 | 0.00000 | 0.000000 |
| 532 | Solid | Neisseriaceae | 0.000000 | 0.00000 | 0.000000 |
| 533 | Solid | Nitrosomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 535 | Solid | Nocardioidaceae | 0.000000 | 0.00000 | 0.000000 |
| 537 | Solid | Oligosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 559 | Solid | Solirubrobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 574 | Solid | Weeksellaceae | 0.000000 | 0.00000 | 0.000000 |
| 577 | Stomach Tube | Acetobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 585 | Stomach Tube | Bacteriovoracaceae | 0.000000 | 0.00000 | 0.000000 |
| 591 | Stomach Tube | Barnesiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 601 | Stomach Tube | Chitinophagaceae | 0.000000 | 0.00000 | 0.000000 |
| 608 | Stomach Tube | Deferribacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 614 | Stomach Tube | Dysgonomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 626 | Stomach Tube | Flavobacteriaceae | 0.000000 | 0.00000 | 0.000000 |
| 628 | Stomach Tube | GZKB124 | 0.000000 | 0.00000 | 0.000000 |
| 629 | Stomach Tube | Hymenobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 630 | Stomach Tube | Kineosporiaceae | 0.000000 | 0.00000 | 0.000000 |
| 641 | Stomach Tube | Methanosarcinaceae | 0.000000 | 0.00000 | 0.000000 |
| 648 | Stomach Tube | Nitrosomonadaceae | 0.000000 | 0.00000 | 0.000000 |
| 652 | Stomach Tube | Oligosphaeraceae | 0.000000 | 0.00000 | 0.000000 |
| 654 | Stomach Tube | p-2534-18B5_gut_group | 0.000000 | 0.00000 | 0.000000 |
| 669 | Stomach Tube | Rhodobacteraceae | 0.000000 | 0.00000 | 0.000000 |
| 678 | Stomach Tube | Spirosomaceae | 0.000000 | 0.00000 | 0.000000 |
| 685 | Stomach Tube | Terasakiellaceae | 0.000000 | 0.00000 | 0.000000 |
| 689 | Stomach Tube | Weeksellaceae | 0.000000 | 0.00000 | 0.000000 |
These are the families found in all samples sorted by decending order of mean relative abundance. Next we will graph out some of the different fam based on their abundance ranges.
We will have a closer look at the familes present in fecal samples.
These are the relative abundance of families found in fecal samples. Next we will graph out these families.
Intially, we can see that there is more Bacteroidaceae and Peptostreptococcaceae in fecal samples compared to rumen samples.
| Sample_Type | Family | mean | sd | sem | |
|---|---|---|---|---|---|
| 1 | Feces | Bacteroidaceae | 7.4037510 | 0.8711443 | 0.2514777 |
| 14 | Grab Sample | Bacteroidaceae | 0.0355318 | 0.0298742 | 0.0086239 |
| 27 | Liquid Strained | Bacteroidaceae | 0.0376197 | 0.0385991 | 0.0111426 |
| 40 | Liquid Unstrained | Bacteroidaceae | 0.0499720 | 0.0397877 | 0.0140671 |
| 53 | Solid | Bacteroidaceae | 0.0275221 | 0.0236625 | 0.0068308 |
| 66 | Stomach Tube | Bacteroidaceae | 0.0710867 | 0.1147546 | 0.0331268 |
| Sample_Type | Family | mean | sd | sem | |
|---|---|---|---|---|---|
| 8 | Feces | Peptostreptococcaceae | 2.8945224 | 0.8990991 | 0.2595475 |
| 21 | Grab Sample | Peptostreptococcaceae | 0.0273192 | 0.0178096 | 0.0051412 |
| 34 | Liquid Strained | Peptostreptococcaceae | 0.0365307 | 0.0322717 | 0.0093160 |
| 47 | Liquid Unstrained | Peptostreptococcaceae | 0.0322039 | 0.0175574 | 0.0062075 |
| 60 | Solid | Peptostreptococcaceae | 0.0327935 | 0.0206118 | 0.0059501 |
| 73 | Stomach Tube | Peptostreptococcaceae | 0.0435303 | 0.0159367 | 0.0046005 |
Conversely, there is more Veillonellaceae and Fibrobacteraceae in rumen samples compared to feces.
| Sample_Type | Family | mean | sd | sem | |
|---|---|---|---|---|---|
| 13 | Feces | Veillonellaceae | 0.0031847 | 0.0059171 | 0.0017081 |
| 26 | Grab Sample | Veillonellaceae | 0.7480463 | 0.1859221 | 0.0536711 |
| 39 | Liquid Strained | Veillonellaceae | 2.1133656 | 0.5698565 | 0.1645034 |
| 52 | Liquid Unstrained | Veillonellaceae | 1.5589519 | 0.8019100 | 0.2835180 |
| 65 | Solid | Veillonellaceae | 0.3685489 | 0.1024515 | 0.0295752 |
| 78 | Stomach Tube | Veillonellaceae | 0.6770020 | 0.4122323 | 0.1190012 |
| Sample_Type | Family | mean | sd | sem | |
|---|---|---|---|---|---|
| 5 | Feces | Fibrobacteraceae | 0.0186986 | 0.0180463 | 0.0052095 |
| 18 | Grab Sample | Fibrobacteraceae | 2.2866939 | 0.5464401 | 0.1577437 |
| 31 | Liquid Strained | Fibrobacteraceae | 2.0179385 | 0.7904481 | 0.2281827 |
| 44 | Liquid Unstrained | Fibrobacteraceae | 1.0178780 | 0.6578643 | 0.2325902 |
| 57 | Solid | Fibrobacteraceae | 1.5059297 | 0.6251762 | 0.1804728 |
| 70 | Stomach Tube | Fibrobacteraceae | 0.3770986 | 0.2593853 | 0.0748781 |
I will make an interactive bubble graph for the lower families
Next we are going to do some exploratory analysis of all sample types.
Now we will take a closer look at the Archeaon populations.
## [1] "These are the Classes in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteria" "Thermoplasmata" "Methanomicrobia"
## [1] "These are the Orders in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteriales" "Methanomassiliicoccales"
## [3] "Methanosarcinales" "Methanomicrobiales"
## [1] "These are the Families in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteriaceae" "Methanomethylophilaceae"
## [3] "Methanosarcinaceae" "Methanocorpusculaceae"
## [1] "These are the Genera in the Kingdom Archaea found in all sample types"
## [1] NA "Methanobrevibacter"
## [3] "Methanosphaera" "Candidatus_Methanomethylophilus"
## [5] "Methanimicrococcus" "Methanocorpusculum"
## [1] "These are the Species in the Kingdom Archaea found in all sample types"
## [1] NA
Looking at the relative abundances of archaeal genera in all samples.
| Sample_Type | Genus | mean | sd | sem | |
|---|---|---|---|---|---|
| 13 | Liquid Strained | Methanobrevibacter | 94.3304 | 2.7636 | 0.7978 |
| 18 | Liquid Unstrained | Methanobrevibacter | 91.9836 | 2.4326 | 0.8600 |
| 28 | Stomach Tube | Methanobrevibacter | 90.6458 | 2.8016 | 0.8088 |
| 8 | Grab Sample | Methanobrevibacter | 88.8381 | 3.0998 | 0.8948 |
| 23 | Solid | Methanobrevibacter | 87.1990 | 6.2745 | 1.8113 |
| 3 | Feces | Methanobrevibacter | 82.6272 | 13.4013 | 3.8686 |
| 4 | Feces | Methanocorpusculum | 13.8867 | 13.1204 | 3.7875 |
| 25 | Solid | Methanosphaera | 12.3900 | 5.6762 | 1.6386 |
| 10 | Grab Sample | Methanosphaera | 10.9553 | 3.0536 | 0.8815 |
| 30 | Stomach Tube | Methanosphaera | 9.0903 | 2.9570 | 0.8536 |
| 20 | Liquid Unstrained | Methanosphaera | 6.5510 | 2.5410 | 0.8984 |
| 15 | Liquid Strained | Methanosphaera | 5.1476 | 2.8505 | 0.8229 |
| 5 | Feces | Methanosphaera | 3.4862 | 4.7416 | 1.3688 |
| 16 | Liquid Unstrained | Candidatus_Methanomethylophilus | 1.2983 | 1.2264 | 0.4336 |
| 24 | Solid | Methanocorpusculum | 0.3248 | 0.7518 | 0.2170 |
| 11 | Liquid Strained | Candidatus_Methanomethylophilus | 0.2623 | 0.5970 | 0.1724 |
| 14 | Liquid Strained | Methanocorpusculum | 0.2010 | 0.3275 | 0.0945 |
| 19 | Liquid Unstrained | Methanocorpusculum | 0.1670 | 0.3097 | 0.1095 |
| 29 | Stomach Tube | Methanocorpusculum | 0.1416 | 0.2746 | 0.0793 |
| 6 | Grab Sample | Candidatus_Methanomethylophilus | 0.1366 | 0.4732 | 0.1366 |
| 26 | Stomach Tube | Candidatus_Methanomethylophilus | 0.1222 | 0.3278 | 0.0946 |
| 9 | Grab Sample | Methanocorpusculum | 0.0700 | 0.2426 | 0.0700 |
| 21 | Solid | Candidatus_Methanomethylophilus | 0.0678 | 0.2347 | 0.0678 |
| 12 | Liquid Strained | Methanimicrococcus | 0.0587 | 0.2033 | 0.0587 |
| 22 | Solid | Methanimicrococcus | 0.0184 | 0.0636 | 0.0184 |
| 1 | Feces | Candidatus_Methanomethylophilus | 0.0000 | 0.0000 | 0.0000 |
| 2 | Feces | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
| 7 | Grab Sample | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
| 17 | Liquid Unstrained | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
| 27 | Stomach Tube | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
Next we will check if there are certain archeal genera that are found in common between fecal and rumen samples. We will also look to see if there are differences between these two sample types.
## [1] "These taxa are found in both phyloseq objects"
## [1] "Methanobacteriaceae" "Methanocorpusculaceae"
## [1] "These taxa are different between the phyloseq objects"
## [1] "Methanomethylophilaceae" "Methanosarcinaceae"
Next, we look at the relative abundances of genera in rumen samples.
| Sample_Type | Genus | mean | sd | sem | |
|---|---|---|---|---|---|
| 8 | Liquid Strained | Methanobrevibacter | 94.3304 | 2.7636 | 0.7978 |
| 13 | Liquid Unstrained | Methanobrevibacter | 91.9836 | 2.4326 | 0.8600 |
| 23 | Stomach Tube | Methanobrevibacter | 90.6458 | 2.8016 | 0.8088 |
| 3 | Grab Sample | Methanobrevibacter | 88.8381 | 3.0998 | 0.8948 |
| 18 | Solid | Methanobrevibacter | 87.1990 | 6.2745 | 1.8113 |
| 20 | Solid | Methanosphaera | 12.3900 | 5.6762 | 1.6386 |
| 5 | Grab Sample | Methanosphaera | 10.9553 | 3.0536 | 0.8815 |
| 25 | Stomach Tube | Methanosphaera | 9.0903 | 2.9570 | 0.8536 |
| 15 | Liquid Unstrained | Methanosphaera | 6.5510 | 2.5410 | 0.8984 |
| 10 | Liquid Strained | Methanosphaera | 5.1476 | 2.8505 | 0.8229 |
| 11 | Liquid Unstrained | Candidatus_Methanomethylophilus | 1.2983 | 1.2264 | 0.4336 |
| 19 | Solid | Methanocorpusculum | 0.3248 | 0.7518 | 0.2170 |
| 6 | Liquid Strained | Candidatus_Methanomethylophilus | 0.2623 | 0.5970 | 0.1724 |
| 9 | Liquid Strained | Methanocorpusculum | 0.2010 | 0.3275 | 0.0945 |
| 14 | Liquid Unstrained | Methanocorpusculum | 0.1670 | 0.3097 | 0.1095 |
| 24 | Stomach Tube | Methanocorpusculum | 0.1416 | 0.2746 | 0.0793 |
| 1 | Grab Sample | Candidatus_Methanomethylophilus | 0.1366 | 0.4732 | 0.1366 |
| 21 | Stomach Tube | Candidatus_Methanomethylophilus | 0.1222 | 0.3278 | 0.0946 |
| 4 | Grab Sample | Methanocorpusculum | 0.0700 | 0.2426 | 0.0700 |
| 16 | Solid | Candidatus_Methanomethylophilus | 0.0678 | 0.2347 | 0.0678 |
| 7 | Liquid Strained | Methanimicrococcus | 0.0587 | 0.2033 | 0.0587 |
| 17 | Solid | Methanimicrococcus | 0.0184 | 0.0636 | 0.0184 |
| 2 | Grab Sample | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
| 12 | Liquid Unstrained | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
| 22 | Stomach Tube | Methanimicrococcus | 0.0000 | 0.0000 | 0.0000 |
We will do the same for fecal samples.
| Sample_Type | Genus | mean | sd | sem |
|---|---|---|---|---|
| Feces | Methanobrevibacter | 82.63 | 13.40 | 3.87 |
| Feces | Methanocorpusculum | 13.89 | 13.12 | 3.79 |
| Feces | Methanosphaera | 3.49 | 4.74 | 1.37 |
Going to use log transformations for normalizing for library size during exploratory analysis. As this looks appropriate for the “tailed” data. For additional confirmation we could do a the same analysis on ranked values for abundance.
## Saving 7 x 5 in image
The fecal samples pull away from the other samples on the first axis. Liquid strained and unstrained samples move higher on the 2nd axis, but this difference is 1/5th that of the differences between fecal samples and all other samples. Overall, it appears that there is 2-3 “clusters”. Next we will ordinate unifrac distances which will take into account phylogenetic differeces in differences in samples.
From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining 86.7954988% of the variance between the samples.
This is Figure 3. We will calculate the gap statisitic to determine how many clusters are here.
The gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.
Now that we take into account phylogenetic information in the distance metric we see a similar clustering pattern as with the bray-curtis. However, now the difference between fecal and other samples on the 1st axis explain 66.5% of the variation. Also, although not quite as clean there still seems to be 3 “clusters”. If you didn’t have stomach tube samples this would be more clear. Grab sample and solid samples aren’t very different from each other.
For good measure we will look at the unweighted unifrac that puts more weight on rare species as well.
We’ll first let’s check on the eigenvalues.
The eigenvalues here show 2 axis are sufficient to capture most of the total variation.
This gives a similar pattern as the bray-curtis and weighted unifrac. Notice that less of the variation is explained in each axis with the unweighted (total 52.7%) versus the weighted unifrac. The fecal samples are clustered closer together than with the weighted unifrac. Again, we will look at the gap statistic.
Just as before, the gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.
Another way to comparing phylogentic differences is double principal coordinates analysis (DPCoA), which is a phylogenetic ordination method and that provides a biplot representation of both samples and taxonomic categories. The computational time for this is much longer than with the unifrac (i.e. Has to be run on a server).
The eigenvalues here show 2 axis are sufficient to capture most of the total variation.
We see again that the 1st axis corresponds to Rumen vs.fecal samples, while the 2nd axis distinguishes Liquid preparations vs those that get liquid and solid fractions. The biplot suggests that the 1st axis can be interpreted to say: samples that have larger scores on the first axis have a subset of taxa from Bacteroidetes and subset of Firmicutes that is different than rumen samples. Additionally, Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Liquid strained samples are being pulled down on the 2nd axis by Kiritimatiellaeota and a subset of Bacteroidetes.
Again, I have made an interactive Version of this plot that is avaliable here.
Since Firmicutes and Bacteroidetes take up so much of the graph we want to know what other phyla can separate the sample types.
Again, I have made an interactive Version of this plot that is avaliable here.
Now that we have Firmicutes and Bacteroidetes gone we can see that feces are associated with Akkermansiaceae and isn’t associated with Kiritimatiellaeota, Chloroflexi, Fibrobacteraceae and Spirochaetaceae.
First we will look at how the “gold standard” grab sample compares to other sample types. We test all the taxa in our data to see if they are differentially-abundant. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons. Addtionally, it controls for differencs in library sizes.
We will take a broad view and look at phyla that are differentially abundant
Looking at the models from corncob.
## $Bacteria_Tenericutes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.32618 0.08935 -48.418 < 2e-16 ***
## Sample_TypeFeces -0.32385 0.09904 -3.270 0.001844 **
## Sample_TypeStomach Tube 0.14483 0.09009 1.608 0.113558
## Sample_TypeLiquid Strained 0.41839 0.08479 4.934 7.58e-06 ***
## Sample_TypeLiquid Unstrained 0.35318 0.09588 3.684 0.000519 ***
## Sample_TypeSolid -0.20922 0.09627 -2.173 0.034002 *
## CowIDCow_2477 0.11394 0.07278 1.566 0.123058
## CowIDCow_2549 0.02563 0.07502 0.342 0.733939
## CowIDCow_796 -0.05018 0.07647 -0.656 0.514415
## DayDay_7 0.02400 0.06693 0.359 0.721206
## DayDay_9 -0.01661 0.06224 -0.267 0.790558
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.5406 0.2152 -35.04 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -307.82
##
## $Bacteria_Kiritimatiellaeota
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.66083 0.14790 -31.514 < 2e-16 ***
## Sample_TypeFeces -0.19514 0.18212 -1.071 0.288551
## Sample_TypeStomach Tube 0.55100 0.15792 3.489 0.000951 ***
## Sample_TypeLiquid Strained 1.98774 0.13439 14.791 < 2e-16 ***
## Sample_TypeLiquid Unstrained 1.31125 0.15124 8.670 6.19e-12 ***
## Sample_TypeSolid -0.15332 0.17998 -0.852 0.397920
## CowIDCow_2477 0.09767 0.09331 1.047 0.299717
## CowIDCow_2549 -0.14153 0.09935 -1.425 0.159826
## CowIDCow_796 -0.29557 0.10239 -2.887 0.005520 **
## DayDay_7 0.08338 0.09483 0.879 0.382986
## DayDay_9 0.36822 0.08184 4.499 3.49e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.2890 0.1865 -33.72 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -349.59
##
## $Bacteria_Verrucomicrobia
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.860455 0.145912 -40.164 < 2e-16 ***
## Sample_TypeFeces 1.340823 0.130015 10.313 1.48e-14 ***
## Sample_TypeStomach Tube 0.591455 0.144743 4.086 0.000141 ***
## Sample_TypeLiquid Strained 0.159528 0.156768 1.018 0.313242
## Sample_TypeLiquid Unstrained 0.451235 0.161794 2.789 0.007212 **
## Sample_TypeSolid 0.052724 0.157616 0.335 0.739247
## CowIDCow_2477 0.248618 0.105124 2.365 0.021520 *
## CowIDCow_2549 0.169063 0.109513 1.544 0.128275
## CowIDCow_796 0.316604 0.104636 3.026 0.003741 **
## DayDay_7 -0.027690 0.091791 -0.302 0.764025
## DayDay_9 0.005016 0.086490 0.058 0.953961
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.8166 0.2357 -33.16 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -266.88
##
## $Bacteria_Epsilonbacteraeota
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -10.51920 0.75370 -13.957 < 2e-16 ***
## Sample_TypeFeces 2.59059 0.72991 3.549 0.000791 ***
## Sample_TypeStomach Tube 1.84208 0.77336 2.382 0.020646 *
## Sample_TypeLiquid Strained 1.90205 0.76235 2.495 0.015572 *
## Sample_TypeLiquid Unstrained 0.52436 0.87565 0.599 0.551702
## Sample_TypeSolid 0.85753 0.80476 1.066 0.291193
## CowIDCow_2477 0.75178 0.28370 2.650 0.010444 *
## CowIDCow_2549 -0.07158 0.36864 -0.194 0.846743
## CowIDCow_796 -0.53520 0.40013 -1.338 0.186442
## DayDay_7 -0.53806 0.29915 -1.799 0.077466 .
## DayDay_9 0.07371 0.25463 0.289 0.773277
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -11.474 2.969 -3.865 0.000291 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -80.421
##
## $Bacteria_Elusimicrobia
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.97333 0.20177 -34.561 < 2e-16 ***
## Sample_TypeFeces -0.09038 0.22702 -0.398 0.692
## Sample_TypeStomach Tube 0.34659 0.21366 1.622 0.110
## Sample_TypeLiquid Strained 1.20583 0.18644 6.468 2.61e-08 ***
## Sample_TypeLiquid Unstrained 0.95436 0.20218 4.720 1.62e-05 ***
## Sample_TypeSolid 0.30858 0.20944 1.473 0.146
## CowIDCow_2477 0.58131 0.13758 4.225 8.88e-05 ***
## CowIDCow_2549 0.03532 0.15654 0.226 0.822
## CowIDCow_796 -0.12122 0.16197 -0.748 0.457
## DayDay_7 -0.17256 0.13773 -1.253 0.215
## DayDay_9 0.17873 0.11616 1.539 0.130
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.4564 0.2785 -30.37 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -210.21
##
## $Bacteria_Planctomycetes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.95287 0.15019 -46.295 < 2e-16 ***
## Sample_TypeFeces 0.69873 0.14002 4.990 6.2e-06 ***
## Sample_TypeStomach Tube 0.28194 0.15811 1.783 0.0800 .
## Sample_TypeLiquid Strained -0.30166 0.17245 -1.749 0.0857 .
## Sample_TypeLiquid Unstrained -0.06845 0.17834 -0.384 0.7026
## Sample_TypeSolid 0.10523 0.15201 0.692 0.4916
## CowIDCow_2477 -0.13631 0.11419 -1.194 0.2376
## CowIDCow_2549 0.07430 0.11610 0.640 0.5248
## CowIDCow_796 0.11625 0.11074 1.050 0.2984
## DayDay_7 -0.07950 0.10021 -0.793 0.4309
## DayDay_9 -0.03517 0.09700 -0.363 0.7183
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -18.02 49.49 -0.364 0.717
##
##
## Log-likelihood: -163.02
##
## $Bacteria_Patescibacteria
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.22958 0.10429 -50.144 < 2e-16 ***
## Sample_TypeFeces -4.33629 0.50006 -8.672 6.15e-12 ***
## Sample_TypeStomach Tube -0.38750 0.11263 -3.440 0.00110 **
## Sample_TypeLiquid Strained -0.06420 0.10112 -0.635 0.52807
## Sample_TypeLiquid Unstrained 0.06616 0.11269 0.587 0.55949
## Sample_TypeSolid 0.29885 0.09132 3.273 0.00183 **
## CowIDCow_2477 -0.13598 0.09056 -1.502 0.13884
## CowIDCow_2549 -0.23319 0.09478 -2.460 0.01699 *
## CowIDCow_796 0.13796 0.08702 1.585 0.11850
## DayDay_7 0.17327 0.07951 2.179 0.03353 *
## DayDay_9 -0.06957 0.07835 -0.888 0.37837
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.738 0.343 -25.47 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -213.52
##
## $Bacteria_Proteobacteria
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.34791 0.11118 -39.107 < 2e-16 ***
## Sample_TypeFeces -0.41730 0.12915 -3.231 0.002068 **
## Sample_TypeStomach Tube 0.12531 0.11381 1.101 0.275561
## Sample_TypeLiquid Strained 0.91226 0.09900 9.215 8.13e-13 ***
## Sample_TypeLiquid Unstrained 0.54359 0.11377 4.778 1.32e-05 ***
## Sample_TypeSolid -0.03213 0.11691 -0.275 0.784479
## CowIDCow_2477 0.45601 0.08564 5.325 1.85e-06 ***
## CowIDCow_2549 0.32237 0.08849 3.643 0.000591 ***
## CowIDCow_796 -0.13856 0.09773 -1.418 0.161787
## DayDay_7 -0.13382 0.08325 -1.607 0.113582
## DayDay_9 0.23357 0.07003 3.335 0.001517 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.7521 0.1918 -35.2 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -339.24
##
## $Bacteria_Fusobacteria
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -9.40842 0.72991 -12.890 < 2e-16 ***
## Sample_TypeFeces 0.02635 0.91483 0.029 0.977121
## Sample_TypeStomach Tube 3.80213 0.72825 5.221 2.7e-06 ***
## Sample_TypeLiquid Strained 0.66197 0.82281 0.805 0.424494
## Sample_TypeLiquid Unstrained 0.62044 0.98151 0.632 0.529877
## Sample_TypeSolid 0.42278 0.86887 0.487 0.628449
## CowIDCow_2477 -0.79047 0.26869 -2.942 0.004737 **
## CowIDCow_2549 -0.88565 0.27579 -3.211 0.002190 **
## CowIDCow_796 -0.55192 0.27870 -1.980 0.052587 .
## DayDay_7 -0.97230 0.24566 -3.958 0.000215 ***
## DayDay_9 -1.00289 0.27730 -3.617 0.000641 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -10.465 1.562 -6.698 1.09e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -76.012
##
## $Archaea_Euryarchaeota
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.36934 0.14166 -23.784 < 2e-16 ***
## Sample_TypeFeces -1.37244 0.21409 -6.411 3.24e-08 ***
## Sample_TypeStomach Tube 0.27843 0.13998 1.989 0.05159 .
## Sample_TypeLiquid Strained -0.16155 0.15362 -1.052 0.29751
## Sample_TypeLiquid Unstrained -0.23238 0.18171 -1.279 0.20623
## Sample_TypeSolid 0.19658 0.14210 1.383 0.17205
## CowIDCow_2477 -0.39646 0.13020 -3.045 0.00354 **
## CowIDCow_2549 -0.64312 0.14188 -4.533 3.11e-05 ***
## CowIDCow_796 0.03754 0.11753 0.319 0.75060
## DayDay_7 -0.02151 0.11568 -0.186 0.85317
## DayDay_9 -0.09570 0.11006 -0.870 0.38826
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.6966 0.1806 -31.55 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -373.86
##
## $Bacteria_Spirochaetes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.60125 0.23700 -15.195 < 2e-16 ***
## Sample_TypeFeces -1.53490 0.30187 -5.085 4.42e-06 ***
## Sample_TypeStomach Tube -0.83674 0.26859 -3.115 0.00290 **
## Sample_TypeLiquid Strained -0.16348 0.22976 -0.712 0.47971
## Sample_TypeLiquid Unstrained -0.27352 0.27019 -1.012 0.31573
## Sample_TypeSolid -0.72480 0.25765 -2.813 0.00675 **
## CowIDCow_2477 0.06750 0.22101 0.305 0.76119
## CowIDCow_2549 0.22085 0.22116 0.999 0.32230
## CowIDCow_796 -0.20800 0.23062 -0.902 0.37095
## DayDay_7 0.20597 0.20392 1.010 0.31680
## DayDay_9 0.08773 0.18761 0.468 0.64189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.662 0.187 -24.94 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -386.64
##
## $Bacteria_Lentisphaerae
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.0354 0.2514 -27.987 < 2e-16 ***
## Sample_TypeFeces 0.8589 0.2691 3.191 0.00232 **
## Sample_TypeStomach Tube 1.5299 0.2498 6.125 9.52e-08 ***
## Sample_TypeLiquid Strained 2.0078 0.2404 8.353 2.04e-11 ***
## Sample_TypeLiquid Unstrained 1.9137 0.2545 7.519 4.79e-10 ***
## Sample_TypeSolid -0.1782 0.3163 -0.563 0.57539
## CowIDCow_2477 0.2979 0.1344 2.217 0.03073 *
## CowIDCow_2549 -0.3844 0.1600 -2.403 0.01959 *
## CowIDCow_796 -0.3786 0.1589 -2.383 0.02061 *
## DayDay_7 0.1512 0.1390 1.088 0.28111
## DayDay_9 0.2184 0.1219 1.791 0.07865 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.593 0.225 -33.74 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -239.06
##
## $Bacteria_Cyanobacteria
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.677072 0.203395 -32.828 < 2e-16 ***
## Sample_TypeFeces 1.084069 0.195841 5.535 8.55e-07 ***
## Sample_TypeStomach Tube 0.553285 0.216712 2.553 0.0134 *
## Sample_TypeLiquid Strained 1.780932 0.185392 9.606 1.92e-13 ***
## Sample_TypeLiquid Unstrained 1.338819 0.204092 6.560 1.84e-08 ***
## Sample_TypeSolid -0.487660 0.262533 -1.858 0.0685 .
## CowIDCow_2477 0.623051 0.120964 5.151 3.48e-06 ***
## CowIDCow_2549 -0.146135 0.144215 -1.013 0.3153
## CowIDCow_796 0.009669 0.138073 0.070 0.9444
## DayDay_7 -0.098718 0.119096 -0.829 0.4107
## DayDay_9 0.139419 0.103197 1.351 0.1821
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.7710 0.2329 -33.36 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -245.28
##
## $Bacteria_Actinobacteria
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.37305 0.09241 -47.323 < 2e-16 ***
## Sample_TypeFeces -0.99467 0.12296 -8.089 5.51e-11 ***
## Sample_TypeStomach Tube 0.37822 0.08711 4.342 5.98e-05 ***
## Sample_TypeLiquid Strained -0.47105 0.10640 -4.427 4.47e-05 ***
## Sample_TypeLiquid Unstrained -0.14511 0.11206 -1.295 0.201
## Sample_TypeSolid 0.11323 0.09073 1.248 0.217
## CowIDCow_2477 0.06229 0.08059 0.773 0.443
## CowIDCow_2549 -0.01023 0.08326 -0.123 0.903
## CowIDCow_796 -0.06658 0.08437 -0.789 0.433
## DayDay_7 -0.07041 0.07052 -0.998 0.322
## DayDay_9 -0.33301 0.07136 -4.666 1.95e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.758 0.228 -34.03 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -286.95
##
## $Bacteria_Fibrobacteres
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.85541 0.12869 -29.960 < 2e-16 ***
## Sample_TypeFeces -3.66382 0.34094 -10.746 3.16e-15 ***
## Sample_TypeStomach Tube -1.79490 0.19964 -8.991 1.87e-12 ***
## Sample_TypeLiquid Strained -0.20619 0.12115 -1.702 0.094304 .
## Sample_TypeLiquid Unstrained -0.95051 0.17339 -5.482 1.04e-06 ***
## Sample_TypeSolid -0.44792 0.12854 -3.485 0.000965 ***
## CowIDCow_2477 0.20363 0.12806 1.590 0.117426
## CowIDCow_2549 0.04339 0.13403 0.324 0.747362
## CowIDCow_796 -0.06200 0.13730 -0.452 0.653342
## DayDay_7 -0.09475 0.12010 -0.789 0.433470
## DayDay_9 0.09135 0.11044 0.827 0.411705
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.4614 0.2001 -32.28 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -297.24
##
## $Bacteria_Chloroflexi
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.16680 0.08413 -61.413 < 2e-16 ***
## Sample_TypeFeces -2.84256 0.21915 -12.971 < 2e-16 ***
## Sample_TypeStomach Tube 0.14863 0.08110 1.833 0.07217 .
## Sample_TypeLiquid Strained -0.29404 0.08904 -3.302 0.00167 **
## Sample_TypeLiquid Unstrained -0.01259 0.09335 -0.135 0.89320
## Sample_TypeSolid 0.17696 0.07707 2.296 0.02544 *
## CowIDCow_2477 0.03086 0.07226 0.427 0.67099
## CowIDCow_2549 -0.06050 0.07532 -0.803 0.42522
## CowIDCow_796 0.06224 0.07387 0.843 0.40307
## DayDay_7 0.08942 0.06434 1.390 0.17010
## DayDay_9 -0.04975 0.06268 -0.794 0.43073
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -9.3891 0.4459 -21.05 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -223.85
##
## $Bacteria_Synergistetes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.54350 0.19936 -37.839 < 2e-16 ***
## Sample_TypeFeces -4.39512 1.00931 -4.355 5.73e-05 ***
## Sample_TypeStomach Tube -0.36401 0.20607 -1.767 0.08276 .
## Sample_TypeLiquid Strained -0.51760 0.20678 -2.503 0.01526 *
## Sample_TypeLiquid Unstrained -0.56557 0.22408 -2.524 0.01447 *
## Sample_TypeSolid 0.46773 0.16073 2.910 0.00518 **
## CowIDCow_2477 0.42127 0.16165 2.606 0.01171 *
## CowIDCow_2549 0.38915 0.16631 2.340 0.02288 *
## CowIDCow_796 -0.11407 0.18717 -0.609 0.54469
## DayDay_7 0.05518 0.14853 0.372 0.71167
## DayDay_9 0.35590 0.13760 2.586 0.01233 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -18.02 67.71 -0.266 0.791
##
##
## Log-likelihood: -123.07
##
## $Bacteria_Firmicutes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.690866 0.080250 8.609 7.78e-12 ***
## Sample_TypeFeces -0.131144 0.082612 -1.587 0.118038
## Sample_TypeStomach Tube 0.021783 0.083320 0.261 0.794714
## Sample_TypeLiquid Strained -0.847284 0.081895 -10.346 1.31e-14 ***
## Sample_TypeLiquid Unstrained -0.377057 0.092779 -4.064 0.000152 ***
## Sample_TypeSolid 0.122158 0.084022 1.454 0.151558
## CowIDCow_2477 -0.131287 0.068888 -1.906 0.061814 .
## CowIDCow_2549 -0.088555 0.069290 -1.278 0.206511
## CowIDCow_796 -0.007342 0.069413 -0.106 0.916143
## DayDay_7 -0.043941 0.062793 -0.700 0.486964
## DayDay_9 -0.093202 0.058245 -1.600 0.115187
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.6580 0.1732 -26.89 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -495.27
##
## $Bacteria_Bacteroidetes
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.45985 0.07056 -20.690 < 2e-16 ***
## Sample_TypeFeces 0.63296 0.06994 9.051 1.49e-12 ***
## Sample_TypeStomach Tube 0.03734 0.07467 0.500 0.619
## Sample_TypeLiquid Strained 0.68808 0.06974 9.867 7.42e-14 ***
## Sample_TypeLiquid Unstrained 0.35169 0.08093 4.345 5.91e-05 ***
## Sample_TypeSolid 0.01534 0.07479 0.205 0.838
## CowIDCow_2477 0.09105 0.05875 1.550 0.127
## CowIDCow_2549 0.09216 0.05881 1.567 0.123
## CowIDCow_796 0.08511 0.05861 1.452 0.152
## DayDay_7 -0.01002 0.05289 -0.189 0.850
## DayDay_9 0.03951 0.04918 0.803 0.425
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.2363 0.1756 -29.81 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -467.93
Next and collapse ASVs in the families and determine what families are differentially abundant.
This is a broad over view of the families that are significant differentially abundant in sample types. We will also dig down further and look at the genus and ASV level.
| Phylum | #Significant ASVs | Total ASVs | Percent Significant ASVs |
|---|---|---|---|
| Actinobacteria | 23 | 96 | 23.958333 |
| Bacteroidetes | 56 | 1257 | 4.455052 |
| Chloroflexi | 15 | 39 | 38.461539 |
| Cyanobacteria | 6 | 65 | 9.230769 |
| Elusimicrobia | 3 | 16 | 18.750000 |
| Euryarchaeota | 16 | 44 | 36.363636 |
| Fibrobacteres | 8 | 39 | 20.512821 |
| Firmicutes | 540 | 3095 | 17.447496 |
| Kiritimatiellaeota | 17 | 180 | 9.444444 |
| Lentisphaerae | 3 | 31 | 9.677419 |
| Patescibacteria | 3 | 14 | 21.428571 |
| Proteobacteria | 11 | 219 | 5.022831 |
| Spirochaetes | 8 | 138 | 5.797101 |
| Tenericutes | 15 | 188 | 7.978723 |
| Verrucomicrobia | 1 | 35 | 2.857143 |
| Deferribacteres | 0 | 1 | 0.000000 |
| Epsilonbacteraeota | 0 | 2 | 0.000000 |
| Fusobacteria | 0 | 4 | 0.000000 |
| Gemmatimonadetes | 0 | 1 | 0.000000 |
| Planctomycetes | 0 | 15 | 0.000000 |
| Synergistetes | 0 | 6 | 0.000000 |
There are 725 significantly differentially abundant ASVs with p < 0.05. Most of these ASVs were from the phyla Firmicutes and Bacteroidetes, but that is in part due to them being the dominant ASVs in the data set. As a percentage of ASVs, Chloroflexi and Euryarchaeota played a large role in distinguish different sample types.
We will graph out the significantly different ASVs from these phylums. First, we look at signficantly differentially abundant ASVs Chloroflexi and Euryarchaeota.
Here we can see that the Euryarchaeota that are important for telling samples types apart are all methanogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.
In addition, based on the DPCoA without Bacteroidetes and Firmicutes we can see that Actinobacteria and Spirochaetes also play and important role in distinguishing liquid strained and fecal from grab samples respectively.
Next we examine the different ASVs in the phylum Bacteroidetes and Firmicutes.
This is a graph of the significant differentially abundant ASVs in the phylum Bacteroidetes.
This is a graph of the significant differentially abundant ASVs in the phylum Firmicutes.
Now we will look further up the phylogenetic tree and collapse ASVs into genera and look for genera differentially abundnant.
There are 121 significantly differentially abundant genera with p < 0.05 and 113 with a p < 0.01. After running corncob 158 genera could not be fit with the model, but 134 were fit to the model.
Let’s extract the ASVs and their p-values.
| p_value | ASV | Taxa | |
|---|---|---|---|
| 1 | 1.29e-03 | ASV_1 | Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group |
| 2 | 1.29e-03 | ASV_10 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans |
| 3 | 1.29e-03 | ASV_1006 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea |
| 4 | 1.29e-03 | ASV_1016 | Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis |
| 5 | 1.29e-03 | ASV_103 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1 |
| 6 | 1.29e-03 | ASV_105 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group |
| 7 | 1.29e-03 | ASV_1118 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4 |
| 8 | 1.29e-03 | ASV_1130 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018 |
| 9 | 1.29e-03 | ASV_1132 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group |
| 10 | 1.29e-03 | ASV_1161 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006 |
| 11 | 1.29e-03 | ASV_1169 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus |
| 12 | 1.29e-03 | ASV_117 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus |
| 13 | 1.29e-03 | ASV_120 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002 |
| 14 | 1.29e-03 | ASV_1220 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5 |
| 15 | 1.29e-03 | ASV_1221 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium |
| 16 | 1.29e-03 | ASV_124 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group |
| 18 | 1.29e-03 | ASV_1366 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio |
| 19 | 1.29e-03 | ASV_1372 | Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium |
| 20 | 1.29e-03 | ASV_14 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium |
| 21 | 1.29e-03 | ASV_1403 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella |
| 22 | 1.29e-03 | ASV_1434 | Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum |
| 23 | 1.29e-03 | ASV_1440 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium |
| 24 | 1.29e-03 | ASV_145 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group |
| 25 | 1.29e-03 | ASV_149 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio |
| 27 | 1.29e-03 | ASV_16 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group |
| 28 | 1.29e-03 | ASV_168 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter |
| 29 | 1.29e-03 | ASV_1682 | Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1 |
| 30 | 1.29e-03 | ASV_169 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004 |
| 31 | 1.29e-03 | ASV_172 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809 |
| 32 | 1.29e-03 | ASV_176 | Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas |
| 33 | 1.29e-03 | ASV_183 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014 |
| 34 | 1.29e-03 | ASV_184 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera |
| 35 | 1.29e-03 | ASV_1915 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005 |
| 36 | 1.29e-03 | ASV_192 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group |
| 37 | 1.29e-03 | ASV_199 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella |
| 38 | 1.29e-03 | ASV_2 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group |
| 39 | 1.29e-03 | ASV_20 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1 |
| 40 | 1.29e-03 | ASV_201 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group |
| 42 | 1.29e-03 | ASV_2079 | Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter |
| 43 | 1.29e-03 | ASV_210 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10 |
| 44 | 1.29e-03 | ASV_212 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010 |
| 48 | 1.29e-03 | ASV_22 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella |
| 49 | 1.29e-03 | ASV_2217 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides |
| 50 | 1.29e-03 | ASV_23 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1 |
| 53 | 1.29e-03 | ASV_232 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1 |
| 54 | 1.29e-03 | ASV_246 | Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma |
| 55 | 1.29e-03 | ASV_247 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009 |
| 56 | 1.29e-03 | ASV_248 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group |
| 57 | 1.29e-03 | ASV_25 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio |
| 58 | 1.29e-03 | ASV_2540 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium |
| 59 | 1.29e-03 | ASV_26 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004 |
| 60 | 1.29e-03 | ASV_267 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013 |
| 62 | 1.29e-03 | ASV_29 | Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2 |
| 63 | 1.29e-03 | ASV_298 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax |
| 65 | 1.29e-03 | ASV_3 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005 |
| 66 | 1.29e-03 | ASV_311 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella |
| 67 | 1.29e-03 | ASV_320 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10 |
| 68 | 1.29e-03 | ASV_3270 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens |
| 69 | 1.29e-03 | ASV_330 | Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia |
| 70 | 1.29e-03 | ASV_336 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group |
| 72 | 1.29e-03 | ASV_348 | Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011 |
| 73 | 1.29e-03 | ASV_357 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002 |
| 74 | 1.29e-03 | ASV_36 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides |
| 76 | 1.29e-03 | ASV_37 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter |
| 77 | 1.29e-03 | ASV_376 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group |
| 78 | 1.29e-03 | ASV_399 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2 |
| 79 | 1.29e-03 | ASV_4 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group |
| 80 | 1.29e-03 | ASV_409 | Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea |
| 81 | 1.29e-03 | ASV_418 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium |
| 82 | 1.29e-03 | ASV_428 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia |
| 83 | 1.29e-03 | ASV_442 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium |
| 84 | 1.29e-03 | ASV_450 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter |
| 85 | 1.29e-03 | ASV_457 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008 |
| 86 | 1.29e-03 | ASV_462 | Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium |
| 87 | 1.29e-03 | ASV_471 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium |
| 88 | 1.29e-03 | ASV_474 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001 |
| 89 | 1.29e-03 | ASV_48 | Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia |
| 90 | 1.29e-03 | ASV_510 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella |
| 93 | 1.29e-03 | ASV_560 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6 |
| 94 | 1.29e-03 | ASV_563 | Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium |
| 95 | 1.29e-03 | ASV_57 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia |
| 96 | 1.29e-03 | ASV_60 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes |
| 98 | 1.29e-03 | ASV_622 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium |
| 99 | 1.29e-03 | ASV_636 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009 |
| 100 | 1.29e-03 | ASV_656 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter |
| 101 | 1.29e-03 | ASV_66 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum |
| 102 | 1.29e-03 | ASV_670 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia |
| 103 | 1.29e-03 | ASV_674 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera |
| 104 | 1.29e-03 | ASV_68 | Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter |
| 105 | 1.29e-03 | ASV_7 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter |
| 106 | 1.29e-03 | ASV_71 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2 |
| 107 | 1.29e-03 | ASV_72 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001 |
| 108 | 1.29e-03 | ASV_733 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004 |
| 109 | 1.29e-03 | ASV_757 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1 |
| 110 | 1.29e-03 | ASV_783 | Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group |
| 111 | 1.29e-03 | ASV_8 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum |
| 112 | 1.29e-03 | ASV_819 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor |
| 113 | 1.29e-03 | ASV_83 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9 |
| 114 | 1.29e-03 | ASV_837 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter |
| 116 | 1.29e-03 | ASV_90 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella |
| 117 | 1.29e-03 | ASV_902 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002 |
| 118 | 1.29e-03 | ASV_91 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003 |
| 120 | 1.29e-03 | ASV_953 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group |
| 121 | 1.29e-03 | ASV_963 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter |
| 47 | 2.46e-03 | ASV_2183 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3 |
| 61 | 2.46e-03 | ASV_2731 | Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium |
| 91 | 2.46e-03 | ASV_520 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus |
| 115 | 2.46e-03 | ASV_887 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group |
| 119 | 2.46e-03 | ASV_921 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010 |
| 75 | 3.62e-03 | ASV_3698 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium |
| 97 | 3.62e-03 | ASV_601 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009 |
| 17 | 5.99e-03 | ASV_1258 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006 |
| 52 | 9.51e-03 | ASV_2319 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter |
| 64 | 1.64e-02 | ASV_2981 | Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus |
| 26 | 1.85e-02 | ASV_1509 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus |
| 71 | 1.85e-02 | ASV_3393 | Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus |
| 92 | 2.52e-02 | ASV_534 | Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia |
| 41 | 2.94e-02 | ASV_2068 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1 |
| 46 | 2.94e-02 | ASV_2134 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2 |
| 51 | 3.12e-02 | ASV_2306 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001 |
| 45 | 3.65e-02 | ASV_2120 | Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_CPla-4_termite_group |
These are genera that are differentailly abundant between sample types and their false discovery corrected p-value. ASVs are listed by significance (p < 0.05).
We will now plot out all these taxa in comparison to grab samples.
## x xmin xmax
## 1 -1.11267855 -1.8019687 -0.4233884
## 2 0.01801409 -0.5188173 0.5548455
## 3 -0.88724045 -1.5615566 -0.2129243
## 4 -0.06100509 -0.5700795 0.4480693
## 5 -0.80587250 -1.4864173 -0.1253277
## 6 -4.40965054 -5.4032656 -3.4160355
## taxa
## 1 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 2 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 3 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 4 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 5 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 6 Lachnospiraceae_Lachnospiraceae_ND3007_group
## variable Phylum
## 1 Feces\nDifferential\nAbundance Firmicutes
## 2 Stomach Tube\nDifferential\nAbundance Firmicutes
## 3 Liquid Strained\nDifferential\nAbundance Firmicutes
## 4 Solid\nDifferential\nAbundance Firmicutes
## 5 Liquid Unstrained\nDifferential\nAbundance Firmicutes
## 6 Feces\nDifferential\nAbundance Firmicutes
This is a graph of genera that are significantly differentially abundant across a sample type. The graph is of our model coefficent with a 95% confidence interval. Negative coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have lower relative abundance. Conversely, postive coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have higher relative abundance.
Let’s take a deeper dive into how these gnera separate by phyla.
##
## Actinobacteria Bacteroidetes Chloroflexi
## 7 12 1
## Elusimicrobia Epsilonbacteraeota Euryarchaeota
## 2 1 3
## Fibrobacteres Firmicutes Fusobacteria
## 1 80 1
## Planctomycetes Proteobacteria Spirochaetes
## 2 7 1
## Synergistetes Tenericutes Verrucomicrobia
## 1 1 1
80 of the 121 significantly different taxa are Firmicutes. If we move the p-value to > 0.01 there are 75 significantly different taxa which are Firmicutes. We will graph out just these 80 taxa.
A majority of these genera in the phylum Firmicutes are in the families Ruminococcaceae and Lachnospiraceae.
This is the graph of the genera that are significantly differentially abundant in the phylum Bacteroidetes.
We can look more closely at one of these ASVs (ASV_622) that feces has a strong negative impact on.
## ASV_622
## "Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium"
## OTU Table: [1 taxa and 68 samples]
## taxa are rows
## 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_622 31 32 15 17 19 14 10 8 18 10 10 24 13 14 17 23
## 298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_622 35 14 18 17 15 20 26 34 4 23 25 30 35 19 15 18
## 360 361 362 363 365 366 367 368 369 370 371 372 373 374 375 376
## ASV_622 36 39 10 2 14 0 0 0 0 0 0 0 0 1 0 0
## 378 379 380 381 382 383 384 385 386 387 388 389 390 505 506 507
## ASV_622 0 31 29 37 46 16 35 18 34 48 22 43 6 8 7 11
## 508 509 510 511
## ASV_622 6 54 28 34
This is the feature table for ASV_622, it looks as those there is only one read for Lachnospiraceae Oribacterium in feces.
##
## Call:
## bbdml(formula = ASV_622 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = ps_gen)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -5.57156 0.12016 -46.367
## Sample_TypeFeces -5.55295 1.01064 -5.494
## Sample_TypeStomach Tube -0.27180 0.12128 -2.241
## Sample_TypeLiquid Strained -0.14208 0.11770 -1.207
## Sample_TypeLiquid Unstrained -0.27676 0.13396 -2.066
## Sample_TypeSolid -0.03301 0.10920 -0.302
## CowIDCow_2477 0.21587 0.10444 2.067
## CowIDCow_2549 0.17021 0.10772 1.580
## CowIDCow_796 -0.17494 0.11833 -1.478
## DayDay_7 -0.06593 0.09719 -0.678
## DayDay_9 0.04943 0.09005 0.549
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeFeces 0.000000994 ***
## Sample_TypeStomach Tube 0.0290 *
## Sample_TypeLiquid Strained 0.2324
## Sample_TypeLiquid Unstrained 0.0435 *
## Sample_TypeSolid 0.7636
## CowIDCow_2477 0.0434 *
## CowIDCow_2549 0.1197
## CowIDCow_796 0.1449
## DayDay_7 0.5003
## DayDay_9 0.5852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -9.0948 0.4929 -18.45 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -181.86
Here we see the output of our hypothesis test. Feces is significantly different that other rumen samples. Additionally, both liquid straind and stomach tube samples have significantly lower abundance of this taxa when compared to grab samples. There is individual cow variation, but the day doesn’t make a significant difference.
Let’s graph out the abundance of Lachnospiraceae Oribacterium.
These graphs show that ASV_622 Lachnospiraceae Oribacterium is in lower abundance in fecal samples.
##
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -1.69605 0.09946 -17.052
## Sample_TypeFeces -0.43825 0.11515 -3.806
## Sample_TypeStomach Tube 0.20191 0.10317 1.957
## Sample_TypeLiquid Strained 1.33969 0.09448 14.180
## Sample_TypeLiquid Unstrained 0.77679 0.10850 7.159
## Sample_TypeSolid 0.03152 0.10552 0.299
## CowIDCow_2477 0.12762 0.08214 1.554
## CowIDCow_2549 0.11890 0.08238 1.443
## CowIDCow_796 0.01186 0.08332 0.142
## DayDay_7 0.00962 0.07586 0.127
## DayDay_9 0.08982 0.06897 1.302
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeFeces 0.000352 ***
## Sample_TypeStomach Tube 0.055336 .
## Sample_TypeLiquid Strained < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained 0.00000000189 ***
## Sample_TypeSolid 0.766242
## CowIDCow_2477 0.125893
## CowIDCow_2549 0.154474
## CowIDCow_796 0.887356
## DayDay_7 0.899541
## DayDay_9 0.198148
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.6695 0.1762 -26.5 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -434.14
##
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams2)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -1.69605 0.09946 -17.052
## Sample_TypeFeces -0.43825 0.11515 -3.806
## Sample_TypeStomach Tube 0.20191 0.10317 1.957
## Sample_TypeLiquid Strained 1.33969 0.09448 14.180
## Sample_TypeLiquid Unstrained 0.77679 0.10850 7.159
## Sample_TypeSolid 0.03152 0.10552 0.299
## CowIDCow_2477 0.12762 0.08214 1.554
## CowIDCow_2549 0.11890 0.08238 1.443
## CowIDCow_796 0.01186 0.08332 0.142
## DayDay_7 0.00962 0.07586 0.127
## DayDay_9 0.08982 0.06897 1.302
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeFeces 0.000352 ***
## Sample_TypeStomach Tube 0.055336 .
## Sample_TypeLiquid Strained < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained 0.00000000189 ***
## Sample_TypeSolid 0.766242
## CowIDCow_2477 0.125893
## CowIDCow_2549 0.154474
## CowIDCow_796 0.887356
## DayDay_7 0.899541
## DayDay_9 0.198148
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -4.6695 0.1762 -26.5 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -434.14
Hypothesis testing of relative abundance of Prevotellaceae.
##
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -0.65855 0.04447 -14.809
## Sample_TypeFeces 1.76038 0.04717 37.323
## Sample_TypeStomach Tube 0.03498 0.04563 0.767
## Sample_TypeLiquid Strained -0.22649 0.04665 -4.855
## Sample_TypeLiquid Unstrained 0.07624 0.05140 1.483
## Sample_TypeSolid 0.13751 0.04495 3.059
## CowIDCow_2477 0.03856 0.03821 1.009
## CowIDCow_2549 -0.09324 0.03885 -2.400
## CowIDCow_796 0.03687 0.03858 0.956
## DayDay_7 -0.03020 0.03485 -0.867
## DayDay_9 -0.04726 0.03254 -1.452
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeFeces < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.4465
## Sample_TypeLiquid Strained 0.00001 ***
## Sample_TypeLiquid Unstrained 0.1436
## Sample_TypeSolid 0.0034 **
## CowIDCow_2477 0.3172
## CowIDCow_2549 0.0197 *
## CowIDCow_796 0.3433
## DayDay_7 0.3899
## DayDay_9 0.1520
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.0056 0.1917 -31.33 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -402.99
##
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams2)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -0.65855 0.04447 -14.809
## Sample_TypeFeces 1.76038 0.04717 37.323
## Sample_TypeStomach Tube 0.03498 0.04563 0.767
## Sample_TypeLiquid Strained -0.22649 0.04665 -4.855
## Sample_TypeLiquid Unstrained 0.07624 0.05140 1.483
## Sample_TypeSolid 0.13751 0.04495 3.059
## CowIDCow_2477 0.03856 0.03821 1.009
## CowIDCow_2549 -0.09324 0.03885 -2.400
## CowIDCow_796 0.03687 0.03858 0.956
## DayDay_7 -0.03020 0.03485 -0.867
## DayDay_9 -0.04726 0.03254 -1.452
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeFeces < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.4465
## Sample_TypeLiquid Strained 0.00001 ***
## Sample_TypeLiquid Unstrained 0.1436
## Sample_TypeSolid 0.0034 **
## CowIDCow_2477 0.3172
## CowIDCow_2549 0.0197 *
## CowIDCow_796 0.3433
## DayDay_7 0.3899
## DayDay_9 0.1520
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.0056 0.1917 -31.33 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -402.99
Hypothesis testing of relative abundance of Ruminococcaceae.
##
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) 0.042374 0.064372 0.658
## Sample_TypeFeces -1.810536 0.079047 -22.905
## Sample_TypeStomach Tube -0.174821 0.064394 -2.715
## Sample_TypeLiquid Strained -0.947437 0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631 0.075585 -8.595
## Sample_TypeSolid -0.139437 0.064160 -2.173
## CowIDCow_2477 -0.131409 0.057870 -2.271
## CowIDCow_2549 0.004171 0.057745 0.072
## CowIDCow_796 -0.040359 0.057518 -0.702
## DayDay_7 0.014258 0.052239 0.273
## DayDay_9 -0.029545 0.048922 -0.604
## Pr(>|t|)
## (Intercept) 0.5131
## Sample_TypeFeces < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.0088 **
## Sample_TypeLiquid Strained < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained 0.0000000000082 ***
## Sample_TypeSolid 0.0340 *
## CowIDCow_2477 0.0270 *
## CowIDCow_2549 0.9427
## CowIDCow_796 0.4858
## DayDay_7 0.7859
## DayDay_9 0.5483
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.1338 0.1794 -28.62 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -429.01
##
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams2)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) 0.042374 0.064372 0.658
## Sample_TypeFeces -1.810536 0.079047 -22.905
## Sample_TypeStomach Tube -0.174821 0.064394 -2.715
## Sample_TypeLiquid Strained -0.947437 0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631 0.075585 -8.595
## Sample_TypeSolid -0.139437 0.064160 -2.173
## CowIDCow_2477 -0.131409 0.057870 -2.271
## CowIDCow_2549 0.004171 0.057745 0.072
## CowIDCow_796 -0.040359 0.057518 -0.702
## DayDay_7 0.014258 0.052239 0.273
## DayDay_9 -0.029545 0.048922 -0.604
## Pr(>|t|)
## (Intercept) 0.5131
## Sample_TypeFeces < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.0088 **
## Sample_TypeLiquid Strained < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained 0.0000000000082 ***
## Sample_TypeSolid 0.0340 *
## CowIDCow_2477 0.0270 *
## CowIDCow_2549 0.9427
## CowIDCow_796 0.4858
## DayDay_7 0.7859
## DayDay_9 0.5483
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.1338 0.1794 -28.62 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -429.01
Hypothesis testing of relative abundance of Lachnospiraceae.
Richness is defined as an estimate the number of ASVs in a sample. Next we will use breakaway to estimate the number of missing species based on the sequence depth and number of rare taxa in the data. These estimates account for different sequencing depths!
The error bars here are quite large, but this is to be expected as there is a lot of uncertainty in estimating alpha diversity.
Next we will test the hypothesis that different sample types have the same microbial diversity.
## Estimates Standard Errors p-values
## (Intercept) 2021.81504 48.63103 0.000
## Sample_TypeGrab Sample 2097.41821 169.47911 0.000
## Sample_TypeLiquid Strained 2252.37940 185.14713 0.000
## Sample_TypeLiquid Unstrained 2267.87495 160.57081 0.000
## Sample_TypeStomach Tube 1590.78095 118.21733 0.000
## Sample_TypeSolid 1810.28830 123.71986 0.000
## CowIDCow_2477 78.63928 84.39906 0.351
## CowIDCow_2549 156.77270 99.34590 0.115
## CowIDCow_796 -57.60818 106.37136 0.588
## DayDay_7 -36.47393 88.72531 0.681
## DayDay_9 -112.34992 77.42422 0.147
## Estimates Standard Errors p-values
## Sample_TypeFeces 2021.75358 73.87303 0.000
## Sample_TypeGrab Sample 4119.10429 169.47362 0.000
## Sample_TypeLiquid Strained 4274.33138 185.14037 0.000
## Sample_TypeLiquid Unstrained 4289.55899 160.56363 0.000
## Sample_TypeStomach Tube 3612.48064 118.20446 0.000
## Sample_TypeSolid 3832.13025 123.70992 0.000
## CowIDCow_2477 78.70047 84.38617 0.351
## CowIDCow_2549 156.85072 99.33510 0.114
## CowIDCow_796 -57.62115 106.36304 0.588
## DayDay_7 -36.52707 88.71495 0.681
## DayDay_9 -112.31280 77.41588 0.147
## Estimates Standard Errors p-values
## (Intercept) 4119.16582 48.63357 0.000
## Sample_TypeFeces -2097.31618 73.89187 0.000
## Sample_TypeLiquid Strained 155.03662 185.15015 0.402
## Sample_TypeLiquid Unstrained 170.61198 160.57402 0.288
## Sample_TypeStomach Tube -506.48308 118.22309 0.000
## Sample_TypeSolid -286.99295 123.72430 0.020
## CowIDCow_2477 78.61278 84.40483 0.352
## CowIDCow_2549 156.79239 99.35073 0.115
## CowIDCow_796 -57.70879 106.37509 0.587
## DayDay_7 -36.47887 88.72994 0.681
## DayDay_9 -112.31633 77.42795 0.147
When you break the rumen samples up into different sample types betta() estimates the mean species-level diversity are significantly different compared to fecal samples. Neither the cow or day caused a significant shift in species level diversity. When compared to the grab sample the stomach tube and solid samples have significatly less mean species-level diversity.
Evenness is defined as how balanced the ASVs are; in other words do they exist in approximately the same relative abundance (1=very even). DivNet will estimate Shannon diversity in the presence of an ecological/microbial network! It also adjusts for different sequencing depths.
Here we will first look to see if samples types differ.
First, we will graph divnet’s estimation of shannon diversity.
Let’s look at hypothesis testing for DivNet estimates of shannon and diversity.
## [1] "hypothesis test for Shannon diversity"
## Hypothesis testing:
## p-value for global test: 0
## Estimates Standard Errors p-values
## (Intercept) 6.28626928 0.007833397 0.000
## Sample_TypeGrab Sample 0.42233374 0.019789481 0.000
## Sample_TypeLiquid Strained 0.33332816 0.016776556 0.000
## Sample_TypeLiquid Unstrained 0.45963678 0.024974179 0.000
## Sample_TypeSolid 0.40306231 0.014932992 0.000
## Sample_TypeStomach Tube 0.35163894 0.019836911 0.000
## CowIDCow_2477 -0.07519473 0.014980824 0.000
## CowIDCow_2549 -0.03249017 0.015576432 0.037
## CowIDCow_796 -0.06513514 0.018650721 0.000
## DayDay_7 -0.01866298 0.013726526 0.174
## DayDay_9 0.04294924 0.014576081 0.003
## Hypothesis testing:
## p-value for global test: 0
## Estimates Standard Errors p-values
## (Intercept) 6.736599905 0.007388884 0.000
## Sample_TypeFeces -0.409523052 0.041617576 0.000
## Sample_TypeStomach Tube -0.095140434 0.013441522 0.000
## Sample_TypeLiquid Strained -0.090070120 0.017307448 0.000
## Sample_TypeSolid -0.023506296 0.019564916 0.230
## Sample_TypeLiquid Unstrained 0.021480919 0.015079179 0.154
## CowIDCow_2477 -0.095425089 0.017819806 0.000
## CowIDCow_2549 -0.044188813 0.014767877 0.003
## CowIDCow_796 -0.087036353 0.016435309 0.000
## DayDay_7 -0.039248141 0.014234720 0.006
## DayDay_9 0.007514973 0.012613441 0.551
Both the cow and day had a significant effect on evenness. Fecal samples had significantly lower evenness than samples from the rumen.
We will put a graph of the richness and evenness together as a figure for publication
We will plot the bray-curtis distances from Divnet. DivNet uses covariate information to share strength across samples and obtain an estimate about the beta diversity of the ecosystem not the samples.
Graph of estimates of bray-curtis distance from model with day and cowID
Graph of estimates of bray-curtis distance from model without day and cowID.
We will remove other a few sample types to compress the data down and look just at the grab sample and feces.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 5164 taxa and 24 samples ]
## sample_data() Sample Data: [ 24 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 5164 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 5164 tips and 5162 internal nodes ]
After subsetting the data we have 5164 ASVs in 24 samples.
Since we saw in the DPCoA that there were two populations of Firmicutes and Bacteriodests that separated rumen and fecal samples, we can ingestigate whether these are different genera or different species that make up this differences.
## [1] "Found in feces not in GS"
## [1] "Barnesiellaceae" "Chitinophagaceae" "p-2534-18B5_gut_group"
## [4] "GZKB124" "Hymenobacteraceae"
## [1] "Found in GS not in feces"
## [1] "Leuconostocaceae" "Carnobacteriaceae"
## [3] "Aerococcaceae" "Syntrophomonadaceae"
## [5] "Bacteroidetes_BD2-2" "PeH15"
## [7] "M2PB4-65_termite_group" "COB_P4-1_termite_group"
## [9] "Spirosomaceae" "Porphyromonadaceae"
These are the families that are found in one and not the other sample type.
## [1] "Found in feces not in GS"
## [1] "Hungatella" "Coprococcus_3"
## [3] "Lachnospiraceae_NC2004_group" "Cellulosilyticum"
## [5] "Terrisporobacter" "Clostridioides"
## [7] "Paeniclostridium" "Ruminococcaceae_UCG-011"
## [9] "Breznakia" "Allobaculum"
## [11] "Dielma" "Jeotgalicoccus"
## [13] "Lysinibacillus" "Odoribacter"
## [15] "Sanguibacteroides" "Taibaiella"
## [17] "Hymenobacter" "Harryflintia"
## [19] "Negativibacillus" "Fournierella"
## [21] "Anaerofilum" "Pygmaiobacter"
## [23] "Faecalibacterium" "Intestinimonas"
## [25] "Lachnoclostridium_5"
## [1] "Found in GS not in feces"
## [1] "Acetatifactor" "Lachnospiraceae_UCG-006"
## [3] "Shuttleworthia" "Lachnoclostridium_1"
## [5] "Lachnoclostridium_12" "Lachnospira"
## [7] "Lachnospiraceae_NK4B4_group" "GCA-900066575"
## [9] "Veillonellaceae_UCG-001" "Quinella"
## [11] "Schwartzia" "Selenomonas_4"
## [13] "Helcococcus" "Peptoniphilus"
## [15] "Erysipelotrichaceae_UCG-008" "Weissella"
## [17] "Desemzia" "Aerococcus"
## [19] "Pelospora" "Prevotellaceae_YAB2003_group"
## [21] "U29-B03" "Rikenella"
## [23] "Dyadobacter" "Tannerella"
## [25] "Porphyromonas" "Angelakisella"
## [27] "Ruminococcaceae_UCG-001" "CAG-352"
## [29] "Ruminococcaceae_UCG-012"
These are the genera that are found in one and not the other sample type.
## [1] "Found in feces not in GS"
## [1] "sedimentorum" "ramosum" "massiliensis"
## [1] "Found in GS not in feces"
## [1] "intestinalis" "xylanivorans" "fibrisolvens" "hungatei"
## [5] "succinivorans" "lipolyticus" "ovis" "indolicus"
## [9] "equigenerosi" "incerta" "ruminis" "bryantii"
## [13] "hamtensis" "levii"
These are the species that are found in one and not the other sample type.
There are 1134 ASVs that are in feces, which are not in grab samples and there are 2102 ASVs in grab samples that are not in feces.
We test all the taxa in our data to see if they are differentially-abundant or differentially-variable. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons.
Although there are species to species differences between samples we might expect this to be the normal variation in sample collection. Thus, we are most concerned with particular family or generna that might be excluded when sampling via different methods.
As we saw that when we graphed out relative abundance of families we will check to see if these differences are significant after taking into account library size differences. Then we will look lower taxonomically.
## ASV_2
## "Firmicutes_Lachnospiraceae"
## ASV_348
## "Firmicutes_Defluviitaleaceae"
## ASV_23
## "Firmicutes_Veillonellaceae"
## ASV_48
## "Firmicutes_Peptostreptococcaceae"
## ASV_1956
## "Firmicutes_Clostridiales_vadinBB60_group"
## ASV_246
## "Tenericutes_Anaeroplasmataceae"
## ASV_117
## "Firmicutes_Streptococcaceae"
## ASV_2071
## "Firmicutes_Planococcaceae"
## ASV_384
## "Firmicutes_Peptococcaceae"
## ASV_1682
## "Firmicutes_Clostridiaceae_1"
## ASV_442
## "Firmicutes_Acidaminococcaceae"
## ASV_1016
## "Firmicutes_Eubacteriaceae"
## ASV_330
## "Verrucomicrobia_Akkermansiaceae"
## ASV_2079
## "Epsilonbacteraeota_Campylobacteraceae"
## ASV_1100
## "Elusimicrobia_Elusimicrobiaceae"
## ASV_783
## "Planctomycetes_Pirellulaceae"
## ASV_563
## "Elusimicrobia_Endomicrobiaceae"
## ASV_171
## "Proteobacteria_Succinivibrionaceae"
## ASV_1336
## "Proteobacteria_Burkholderiaceae"
## ASV_2314
## "Proteobacteria_Oligoflexaceae"
## ASV_7
## "Euryarchaeota_Methanobacteriaceae"
## ASV_231
## "Euryarchaeota_Methanomethylophilaceae"
## ASV_1434
## "Euryarchaeota_Methanocorpusculaceae"
## ASV_534
## "Proteobacteria_Devosiaceae"
## ASV_29
## "Spirochaetes_Spirochaetaceae"
## ASV_1548
## "Lentisphaerae_Victivallaceae"
## ASV_2068
## "Actinobacteria_Corynebacteriaceae"
## ASV_656
## "Actinobacteria_Coriobacteriales_Incertae_Sedis"
## ASV_172
## "Actinobacteria_Eggerthellaceae"
## ASV_90
## "Actinobacteria_Atopobiaceae"
## ASV_68
## "Fibrobacteres_Fibrobacteraceae"
## ASV_409
## "Chloroflexi_Anaerolineaceae"
## ASV_499
## "Synergistetes_Synergistaceae"
## ASV_1
## "Firmicutes_Christensenellaceae"
## ASV_26
## "Bacteroidetes_Prevotellaceae"
## ASV_36
## "Bacteroidetes_Bacteroidaceae"
## ASV_2770
## "Bacteroidetes_Marinifilaceae"
## ASV_995
## "Bacteroidetes_Muribaculaceae"
## ASV_1084
## "Bacteroidetes_F082"
## ASV_994
## "Bacteroidetes_Sphingobacteriaceae"
## ASV_197
## "Bacteroidetes_Bacteroidales_BS11_gut_group"
## ASV_60
## "Bacteroidetes_Rikenellaceae"
## ASV_572
## "Bacteroidetes_Marinilabiliaceae"
## ASV_536
## "Bacteroidetes_p-251-o5"
## ASV_2217
## "Bacteroidetes_Tannerellaceae"
## ASV_822
## "Bacteroidetes_Paludibacteraceae"
## ASV_651
## "Bacteroidetes_Bacteroidales_RF16_group"
## ASV_3
## "Firmicutes_Ruminococcaceae"
There are 48 families that are significantly different between fecal and grab samples.
These are the families that are significantly lower and higher in abundance.
##
## -1 1
## 30 18
There are 18 families significantly increased and 30 significantly decreased in relative abundance compared to grab samples.
| x | taxa | Family | |
|---|---|---|---|
| 3 | -5.5479763 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae (ASV_23) | Veillonellaceae |
| 41 | -4.8958710 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_BS11_gut_group (ASV_197) | Bacteroidales_BS11_gut_group |
| 43 | -4.8435765 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinilabiliaceae (ASV_572) | Marinilabiliaceae |
| 17 | -4.4552940 | Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae (ASV_563) | Endomicrobiaceae |
| 31 | -4.4179317 | Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae (ASV_68) | Fibrobacteraceae |
| 33 | -4.4073698 | Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae (ASV_499) | Synergistaceae |
| 18 | -3.8406088 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae (ASV_171) | Succinivibrionaceae |
| 22 | -3.8244025 | Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae (ASV_231) | Methanomethylophilaceae |
| 6 | -3.0967818 | Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae (ASV_246) | Anaeroplasmataceae |
| 32 | -2.9542980 | Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae (ASV_409) | Anaerolineaceae |
| 24 | -2.9465011 | Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae (ASV_534) | Devosiaceae |
| 20 | -2.3601932 | Bacteria_Proteobacteria_Deltaproteobacteria_Oligoflexales_Oligoflexaceae (ASV_2314) | Oligoflexaceae |
| 44 | -2.1251118 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_p-251-o5 (ASV_536) | p-251-o5 |
| 28 | -1.9605047 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis (ASV_656) | Coriobacteriales_Incertae_Sedis |
| 30 | -1.8100719 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae (ASV_90) | Atopobiaceae |
| 40 | -1.6584080 | Bacteria_Bacteroidetes_Bacteroidia_Sphingobacteriales_Sphingobacteriaceae (ASV_994) | Sphingobacteriaceae |
| 39 | -1.5196692 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_F082 (ASV_1084) | F082 |
| 25 | -1.5130522 | Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae (ASV_29) | Spirochaetaceae |
| 21 | -1.4923050 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae (ASV_7) | Methanobacteriaceae |
| 1 | -1.4413798 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae (ASV_2) | Lachnospiraceae |
| 27 | -1.3854374 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae (ASV_2068) | Corynebacteriaceae |
| 12 | -1.1462353 | Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae (ASV_1016) | Eubacteriaceae |
| 7 | -1.1093855 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae (ASV_117) | Streptococcaceae |
| 34 | -1.0002190 | Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae (ASV_1) | Christensenellaceae |
| 2 | -0.9622930 | Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae (ASV_348) | Defluviitaleaceae |
| 29 | -0.9606860 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae (ASV_172) | Eggerthellaceae |
| 19 | -0.8850722 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae (ASV_1336) | Burkholderiaceae |
| 11 | -0.6191481 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae (ASV_442) | Acidaminococcaceae |
| 38 | -0.4438094 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Muribaculaceae (ASV_995) | Muribaculaceae |
| 35 | -0.3491789 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae (ASV_26) | Prevotellaceae |
| 16 | 0.7348044 | Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae (ASV_783) | Pirellulaceae |
| 42 | 0.8358951 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae (ASV_60) | Rikenellaceae |
| 37 | 0.9817063 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinifilaceae (ASV_2770) | Marinifilaceae |
| 9 | 1.0539220 | Bacteria_Firmicutes_Clostridia_Clostridiales_Peptococcaceae (ASV_384) | Peptococcaceae |
| 47 | 1.1177019 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_RF16_group (ASV_651) | Bacteroidales_RF16_group |
| 48 | 1.1785720 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae (ASV_3) | Ruminococcaceae |
| 15 | 1.3666778 | Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae (ASV_1100) | Elusimicrobiaceae |
| 10 | 1.6291444 | Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1 (ASV_1682) | Clostridiaceae_1 |
| 45 | 1.7352336 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae (ASV_2217) | Tannerellaceae |
| 5 | 2.2880851 | Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_vadinBB60_group (ASV_1956) | Clostridiales_vadinBB60_group |
| 14 | 2.6322533 | Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae (ASV_2079) | Campylobacteraceae |
| 26 | 3.0609734 | Bacteria_Lentisphaerae_Lentisphaeria_Victivallales_Victivallaceae (ASV_1548) | Victivallaceae |
| 46 | 3.2160642 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Paludibacteraceae (ASV_822) | Paludibacteraceae |
| 8 | 3.3023998 | Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae (ASV_2071) | Planococcaceae |
| 23 | 3.9963476 | Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae (ASV_1434) | Methanocorpusculaceae |
| 4 | 4.5037536 | Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae (ASV_48) | Peptostreptococcaceae |
| 13 | 4.6224111 | Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae (ASV_330) | Akkermansiaceae |
| 36 | 5.3588153 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae (ASV_36) | Bacteroidaceae |
## [1] "Model for Peptostreptococcaceae"
##
## Call:
## bbdml(formula = ASV_48 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.9644 0.3372 -20.655 0.000000000000582 ***
## Sample_TypeFeces 4.3477 0.3223 13.491 0.000000000370577 ***
## CowIDCow_2477 -0.2735 0.1186 -2.305 0.0349 *
## CowIDCow_2549 -0.1772 0.1215 -1.458 0.1641
## CowIDCow_796 0.2097 0.1063 1.972 0.0661 .
## DayDay_7 0.2602 0.1047 2.485 0.0244 *
## DayDay_9 0.4111 0.1024 4.015 0.0010 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.7448 0.4179 -16.14 0.0000000000254 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -83.154
## [1] "Model for Akkermansiaceae"
##
## Call:
## bbdml(formula = ASV_330 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.27005 0.64229 -12.876 0.000000000737 ***
## Sample_TypeFeces 4.71006 0.61628 7.643 0.000000997988 ***
## CowIDCow_2477 0.30451 0.23539 1.294 0.2142
## CowIDCow_2549 0.59090 0.23030 2.566 0.0207 *
## CowIDCow_796 0.51348 0.22589 2.273 0.0372 *
## DayDay_7 0.04634 0.18572 0.250 0.8061
## DayDay_9 -0.08257 0.19196 -0.430 0.6728
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.061 0.451 -13.44 0.000000000392 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -68.472
## [1] "Model for Bacteroidaceae"
##
## Call:
## bbdml(formula = ASV_36 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.58850 0.27165 -24.254 0.000000000000048 ***
## Sample_TypeFeces 5.48235 0.26807 20.452 0.000000000000678 ***
## CowIDCow_2477 -0.22519 0.05542 -4.064 0.000903 ***
## CowIDCow_2549 -0.08155 0.05860 -1.392 0.183085
## CowIDCow_796 -0.24183 0.05468 -4.423 0.000427 ***
## DayDay_7 -0.13691 0.04904 -2.792 0.013058 *
## DayDay_9 -0.11920 0.04946 -2.410 0.028333 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.6553 0.5714 -13.4 0.000000000411 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -82.185
## [1] "Model for Veillonellaceae"
##
## Call:
## bbdml(formula = ASV_23 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.75237 0.11655 -32.195 0.000000000000000564 ***
## Sample_TypeFeces -5.62348 0.57920 -9.709 0.000000041362350627 ***
## CowIDCow_2477 0.33876 0.13059 2.594 0.01958 *
## CowIDCow_2549 0.20408 0.13773 1.482 0.15782
## CowIDCow_796 0.08529 0.13895 0.614 0.54797
## DayDay_7 -0.38034 0.10482 -3.629 0.00226 **
## DayDay_9 -0.27460 0.11020 -2.492 0.02406 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -18.02 102.87 -0.175 0.863
##
##
## Log-likelihood: -45.747
## [1] "Model for Marinifilaceae"
##
## Call:
## bbdml(formula = ASV_2770 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.9769 0.3349 -20.834 0.000000000000509 ***
## Sample_TypeFeces 0.9070 0.2727 3.327 0.00427 **
## CowIDCow_2477 -0.7115 0.3571 -1.992 0.06369 .
## CowIDCow_2549 -0.2403 0.3590 -0.669 0.51287
## CowIDCow_796 0.4016 0.2624 1.531 0.14539
## DayDay_7 -0.2217 0.2529 -0.877 0.39365
## DayDay_9 -0.3895 0.2695 -1.445 0.16769
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -18.02 116.78 -0.154 0.879
##
##
## Log-likelihood: -43.09
## [1] "Model for Bacteroidales_BS11_gut_group"
##
## Call:
## bbdml(formula = ASV_197 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.85845 0.15016 -25.696 0.0000000000000195 ***
## Sample_TypeFeces -4.77223 0.54227 -8.801 0.0000001575346194 ***
## CowIDCow_2477 -0.03706 0.16834 -0.220 0.8285
## CowIDCow_2549 -0.34477 0.18772 -1.837 0.0849 .
## CowIDCow_796 -0.02837 0.16832 -0.169 0.8682
## DayDay_7 -0.26834 0.15820 -1.696 0.1092
## DayDay_9 0.23722 0.14364 1.651 0.1181
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.0549 0.8796 -9.157 0.0000000921 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -52.524
## [1] "Model for Fibrobacteraceae"
##
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.647050 0.419377 -6.312 0.0000103 ***
## Sample_TypeFeces -1.669545 0.361365 -4.620 0.000284 ***
## CowIDCow_2477 0.003809 0.437963 0.009 0.993168
## CowIDCow_2549 0.932873 0.414670 2.250 0.038898 *
## CowIDCow_796 -0.121804 0.441738 -0.276 0.786278
## DayDay_7 0.712349 0.360838 1.974 0.065887 .
## DayDay_9 -0.148602 0.383329 -0.388 0.703375
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.2789 0.3615 -9.071 0.000000105 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -134.17
## [1] "Model for Spirochaetaceae"
##
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.79001 0.11492 -24.279 0.0000000000000473 ***
## Sample_TypeFeces -4.49686 0.35791 -12.564 0.0000000010544203 ***
## CowIDCow_2477 0.31230 0.13279 2.352 0.0318 *
## CowIDCow_2549 0.07762 0.14036 0.553 0.5879
## CowIDCow_796 0.32862 0.13328 2.466 0.0254 *
## DayDay_7 -0.05507 0.11132 -0.495 0.6275
## DayDay_9 -0.01997 0.11247 -0.178 0.8613
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.8347 0.4993 -13.69 0.000000000299 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -78.079
## [1] "Model for Christensenellaceae"
##
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.32931 0.16785 1.962 0.0674 .
## Sample_TypeFeces -1.49195 0.13292 -11.224 0.00000000538 ***
## CowIDCow_2477 0.07971 0.18096 0.440 0.6655
## CowIDCow_2549 -0.32060 0.18676 -1.717 0.1053
## CowIDCow_796 -0.01653 0.17810 -0.093 0.9272
## DayDay_7 -0.23819 0.15907 -1.497 0.1538
## DayDay_9 0.02002 0.15683 0.128 0.9000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.8665 0.2923 -13.23 0.000000000495 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -155.04
## [1] "Model for Rikenellaceae"
##
## Call:
## bbdml(formula = ASV_60 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_fams)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.15572 0.09990 -11.568 0.000000003491 ***
## Sample_TypeFeces 1.00619 0.07487 13.439 0.000000000392 ***
## CowIDCow_2477 -0.02057 0.10380 -0.198 0.8454
## CowIDCow_2549 -0.19311 0.10515 -1.837 0.0849 .
## CowIDCow_796 0.01051 0.10297 0.102 0.9200
## DayDay_7 -0.07651 0.08972 -0.853 0.4064
## DayDay_9 -0.01074 0.09039 -0.119 0.9069
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.0415 0.3071 -16.41 0.0000000000197 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -141.9
We will look at a couple genera.
## [1] "Model for Fibrobacter"
##
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_gen)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.02493 0.28801 -0.087 0.9321
## Sample_TypeFeces -2.73012 0.33675 -8.107 0.000000466 ***
## CowIDCow_2477 0.49871 0.32837 1.519 0.1483
## CowIDCow_2549 -0.59569 0.33729 -1.766 0.0964 .
## CowIDCow_796 0.38756 0.32444 1.195 0.2497
## DayDay_7 -0.35679 0.28192 -1.266 0.2238
## DayDay_9 0.18459 0.28904 0.639 0.5321
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.1612 0.3596 -8.79 0.00000016 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -77.336
## [1] "Model for Treponema_2"
##
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = sig_gen)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.02493 0.28801 0.087 0.9321
## Sample_TypeFeces 2.73012 0.33675 8.107 0.000000466 ***
## CowIDCow_2477 -0.49871 0.32837 -1.519 0.1483
## CowIDCow_2549 0.59569 0.33729 1.766 0.0964 .
## CowIDCow_796 -0.38756 0.32444 -1.195 0.2497
## DayDay_7 0.35679 0.28192 1.266 0.2238
## DayDay_9 -0.18459 0.28904 -0.639 0.5321
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.1612 0.3596 -8.79 0.00000016 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -77.336
These are graphs of the relative abundance of families significantly differently between fecal and grab samples. This is figure 6.
After running corncob 131 genera could not be fit with the model, but 130 were fit to the model and 114 were significanlty differentially abundant genera and 657significanlty differentially abundant ASVs.
We will look into taxa could not be fit to the model and see if we can determine why.
## [1] 131
## OTU Table: [131 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_4633 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2
## ASV_429 2 2 3 2 4 2 12 13 5 5 6 6 0 0 0 0
## ASV_5279 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0
## ASV_669 3 7 2 6 7 8 12 8 3 6 4 2 0 0 0 0
## ASV_713 0 0 0 0 0 0 0 0 0 0 0 0 28 20 27 22
## ASV_4679 0 0 0 0 1 1 0 0 2 0 0 1 0 0 0 0
## ASV_878 6 5 4 0 0 3 0 0 0 4 6 2 0 0 0 0
## ASV_4288 0 2 0 1 1 0 1 2 0 0 0 1 0 0 0 0
## ASV_793 15 7 7 12 16 15 14 14 9 17 13 19 0 0 0 0
## ASV_4973 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_2583 1 2 1 1 1 0 2 1 0 5 0 4 0 0 0 0
## ASV_5230 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1393 0 0 0 0 0 0 0 0 0 0 0 0 7 19 14 5
## ASV_2417 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0
## ASV_456 10 0 4 7 3 7 5 7 6 2 1 3 0 0 0 0
## ASV_4284 1 1 0 3 4 3 4 1 4 4 1 1 0 0 0 0
## ASV_2244 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_5146 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_2322 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 1
## ASV_113 0 0 0 0 0 0 0 0 0 0 0 0 33 31 32 47
## ASV_147 0 0 0 0 0 0 0 0 0 0 0 0 11 33 10 30
## ASV_4383 0 0 0 1 2 1 0 0 0 0 1 0 0 0 0 0
## ASV_4854 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5567 0 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0
## ASV_5123 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5418 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1
## ASV_4130 0 0 0 0 0 1 2 1 4 1 1 1 0 0 0 0
## ASV_1759 1 1 4 0 0 0 3 3 2 1 0 0 0 0 0 0
## ASV_413 0 1 1 0 0 1 0 0 0 0 0 1 0 0 0 0
## ASV_1612 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 1
## ASV_4673 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_3469 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3393 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_5204 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2981 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4744 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0
## ASV_4508 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_3129 0 1 2 2 1 1 0 0 0 0 0 0 0 0 0 0
## ASV_5524 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_4013 0 0 0 0 1 0 0 2 1 2 0 0 0 0 0 0
## ASV_574 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1728 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_276 2 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0
## ASV_511 3 4 3 1 1 0 5 7 4 2 2 3 0 0 0 0
## ASV_1518 1 0 2 0 0 2 0 2 0 2 2 0 0 0 0 0
## ASV_171 30 18 14 8 9 10 6 13 8 4 6 6 0 0 0 0
## ASV_1373 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0
## ASV_1078 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4258 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1336 0 0 0 0 0 0 0 0 0 0 0 0 4 6 5 6
## ASV_5356 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4
## ASV_2174 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_2658 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_4109 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_1947 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_503 0 1 1 1 0 0 0 0 1 1 0 0 0 0 0 0
## ASV_424 3 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_2419 0 0 1 2 1 1 0 0 0 0 0 0 0 0 0 0
## ASV_2915 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4015 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4126 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0
## ASV_3435 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_2130 0 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0
## ASV_4324 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4076 0 0 0 0 0 0 0 0 0 0 0 0 7 2 3 5
## ASV_5222 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_4211 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3936 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3276 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_5262 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_221 1 0 2 0 1 1 2 2 0 0 0 0 0 0 0 0
## ASV_2401 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0
## ASV_4992 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1856 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1
## ASV_3262 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5025 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_2037 0 0 0 0 1 0 0 0 3 0 0 0 0 0 0 0
## ASV_5107 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_5555 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3123 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
## ASV_2044 0 1 2 0 1 0 0 0 0 1 0 1 0 0 0 0
## ASV_4913 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1389 2 1 0 3 4 6 3 5 4 1 1 1 0 0 0 0
## ASV_3684 0 0 0 0 0 0 0 0 0 0 0 0 1 4 1 1
## ASV_901 2 0 1 1 4 1 1 0 5 0 2 1 0 0 0 0
## ASV_578 2 4 6 6 5 0 3 4 4 2 2 3 0 0 0 0
## ASV_5600 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2
## ASV_4378 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1247 0 0 0 0 0 0 0 0 0 0 0 0 10 5 17 5
## ASV_3201 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_1042 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 1
## ASV_2594 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1307 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## ASV_2550 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1306 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_3273 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_520 1 0 2 0 0 0 2 0 1 0 0 0 0 0 0 1
## ASV_3119 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_5589 0 1 0 0 1 0 1 0 0 1 0 0 0 0 0 0
## ASV_2687 0 0 0 0 0 0 0 0 0 0 0 0 2 6 2 2
## ASV_4612 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_5602 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_499 3 7 2 9 3 3 2 3 2 4 5 0 0 0 0 0
## ASV_2617 1 0 0 0 0 0 1 1 0 1 2 0 0 0 0 0
## ASV_2770 0 0 0 0 0 0 0 0 0 0 0 0 2 3 3 3
## ASV_5521 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_1658 3 4 1 2 0 3 3 1 0 3 2 3 0 0 0 0
## ASV_1213 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_994 0 0 1 0 2 0 0 1 0 0 0 0 0 0 0 0
## ASV_5192 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_5568 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_2880 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0
## ASV_3146 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_5036 0 0 0 0 0 0 1 0 0 2 0 0 0 0 0 0
## ASV_4270 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_4849 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_2544 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 6
## ASV_1565 0 0 1 7 1 0 2 3 1 3 1 3 0 0 0 0
## ASV_1448 0 0 0 0 0 0 0 0 0 0 0 0 9 8 2 7
## ASV_1756 0 0 0 0 0 0 0 0 0 0 0 0 2 4 2 1
## ASV_4771 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0
## ASV_5492 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2759 0 0 0 0 0 0 0 0 0 0 0 0 3 2 3 4
## ASV_4822 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 2
## ASV_5006 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1
## ASV_2171 2 0 2 7 1 0 2 1 2 0 1 1 0 0 0 0
## ASV_3188 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0
## ASV_2318 1 2 3 1 2 7 1 1 1 0 5 4 0 0 0 0
## ASV_4340 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
## ASV_5426 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 370 371 372 373 374 375 376 378
## ASV_4633 3 1 6 1 1 0 0 0
## ASV_429 0 0 0 0 0 0 0 0
## ASV_5279 2 0 3 0 2 0 1 1
## ASV_669 0 0 0 0 0 0 0 0
## ASV_713 26 35 64 46 48 20 23 15
## ASV_4679 0 0 0 0 0 0 0 0
## ASV_878 0 0 0 0 0 0 0 0
## ASV_4288 0 0 0 0 0 0 0 0
## ASV_793 0 0 0 0 0 0 0 0
## ASV_4973 0 0 0 0 0 0 0 0
## ASV_2583 0 0 0 0 0 0 0 0
## ASV_5230 0 0 0 0 0 1 0 0
## ASV_1393 4 14 26 7 7 5 7 2
## ASV_2417 0 0 0 0 0 0 1 0
## ASV_456 0 0 0 0 0 0 0 0
## ASV_4284 0 0 0 0 0 0 0 0
## ASV_2244 0 0 0 0 0 0 0 0
## ASV_5146 0 0 0 0 0 0 0 0
## ASV_2322 4 3 4 4 6 8 2 7
## ASV_113 69 55 101 85 70 61 78 53
## ASV_147 35 31 74 84 52 64 93 54
## ASV_4383 1 0 0 0 0 0 0 0
## ASV_4854 0 0 0 0 0 0 0 0
## ASV_5567 0 0 0 0 0 0 0 0
## ASV_5123 1 0 2 1 1 1 0 3
## ASV_5340 0 0 1 0 0 0 0 0
## ASV_5418 1 2 0 0 0 1 0 0
## ASV_4130 0 0 0 0 0 0 0 0
## ASV_1759 0 0 0 0 0 0 0 0
## ASV_413 0 0 0 0 0 0 0 0
## ASV_1612 0 0 1 0 1 0 2 0
## ASV_4673 0 0 0 0 0 0 0 0
## ASV_3469 0 0 0 0 0 0 0 0
## ASV_3393 0 0 1 0 0 0 0 0
## ASV_5204 0 0 1 0 0 0 0 0
## ASV_2981 0 0 0 0 1 0 0 0
## ASV_4744 2 2 1 0 1 1 5 1
## ASV_4508 0 0 4 0 1 0 0 0
## ASV_3129 0 0 0 0 0 0 0 0
## ASV_5524 0 0 0 0 3 1 0 0
## ASV_4013 0 1 1 0 1 0 0 0
## ASV_574 0 0 0 0 0 0 0 0
## ASV_1728 0 0 0 0 0 1 0 0
## ASV_276 0 0 0 0 0 1 0 0
## ASV_511 0 0 0 0 0 0 0 0
## ASV_1518 0 0 0 0 0 0 0 0
## ASV_171 0 0 0 0 0 0 0 0
## ASV_1373 0 0 0 0 0 0 0 0
## ASV_1078 0 0 0 0 0 0 0 0
## ASV_4258 0 0 0 0 0 0 0 1
## ASV_1336 5 6 6 6 16 9 13 5
## ASV_5356 0 0 0 0 0 2 1 1
## ASV_2174 0 0 0 0 0 0 0 0
## ASV_2658 0 0 0 0 0 0 0 0
## ASV_4109 0 0 0 0 0 0 0 0
## ASV_1947 0 0 0 0 0 0 0 0
## ASV_503 0 0 0 0 0 0 0 0
## ASV_424 0 0 0 0 0 0 0 0
## ASV_2419 0 0 0 0 0 0 0 0
## ASV_2915 0 0 0 0 0 0 0 0
## ASV_4015 0 0 0 0 0 0 0 1
## ASV_4126 0 0 0 0 0 0 0 0
## ASV_3435 0 0 0 0 0 0 0 0
## ASV_2130 0 0 0 0 0 0 0 0
## ASV_4324 6 2 0 0 1 2 2 3
## ASV_4076 2 5 4 4 1 2 1 0
## ASV_5222 0 0 0 0 0 0 0 0
## ASV_4211 0 1 0 0 1 0 0 1
## ASV_3936 0 0 0 0 0 0 0 0
## ASV_3276 0 0 0 0 0 0 0 0
## ASV_5262 0 0 0 0 0 0 0 0
## ASV_221 0 0 0 0 0 0 0 0
## ASV_2401 0 0 0 0 0 0 0 0
## ASV_4992 0 0 0 0 0 0 0 0
## ASV_1856 1 0 0 1 0 0 0 0
## ASV_3262 0 0 0 0 0 0 0 0
## ASV_5025 0 0 0 0 1 0 0 0
## ASV_2037 0 0 0 0 0 0 0 0
## ASV_5107 0 0 0 0 0 0 0 0
## ASV_5555 0 0 0 1 0 0 0 0
## ASV_3123 0 0 0 0 0 0 0 0
## ASV_2044 0 0 0 0 0 0 0 0
## ASV_4913 1 0 0 0 3 2 1 0
## ASV_1389 0 0 0 0 0 0 0 0
## ASV_3684 3 1 3 5 3 2 1 1
## ASV_901 0 0 0 0 0 0 0 0
## ASV_578 0 0 0 0 0 0 0 0
## ASV_5600 0 0 0 0 0 0 0 0
## ASV_4378 0 1 0 0 0 0 0 0
## ASV_1247 6 6 16 7 16 9 16 11
## ASV_3201 0 0 0 0 0 0 0 0
## ASV_1042 0 0 0 0 0 0 0 0
## ASV_2594 0 0 0 0 0 0 0 0
## ASV_1307 0 0 0 0 0 0 0 0
## ASV_2550 0 0 0 0 0 0 0 1
## ASV_1306 0 1 0 0 0 0 0 0
## ASV_3273 0 0 0 0 0 0 0 0
## ASV_520 0 0 1 0 0 0 0 0
## ASV_3119 0 0 0 0 0 0 0 0
## ASV_5589 0 0 0 0 0 0 0 0
## ASV_2687 3 5 2 6 1 1 1 2
## ASV_4612 0 0 0 0 0 0 0 0
## ASV_5602 2 0 0 0 0 0 0 0
## ASV_499 0 0 0 0 0 0 0 0
## ASV_2617 0 0 0 0 0 0 0 0
## ASV_2770 2 3 10 9 12 10 2 6
## ASV_5521 0 0 1 1 1 1 0 0
## ASV_1658 0 0 0 0 0 0 0 0
## ASV_1213 1 0 0 0 0 0 0 0
## ASV_994 1 0 0 0 0 0 0 0
## ASV_5192 0 0 0 0 0 0 0 0
## ASV_5568 0 0 0 0 0 0 0 0
## ASV_2880 0 0 0 0 0 0 0 0
## ASV_3146 0 0 0 0 0 0 0 0
## ASV_5036 0 0 0 0 0 0 0 0
## ASV_4270 0 0 0 0 0 0 0 0
## ASV_4849 0 0 1 0 0 2 3 0
## ASV_2544 4 5 17 15 7 9 12 9
## ASV_1565 0 0 0 0 0 0 0 0
## ASV_1448 11 7 9 5 5 6 7 4
## ASV_1756 4 2 17 8 5 5 8 8
## ASV_4771 0 0 1 0 0 0 0 0
## ASV_5492 0 0 0 1 2 1 1 0
## ASV_2759 8 5 5 4 1 5 7 7
## ASV_4822 1 0 2 2 0 1 3 1
## ASV_5006 2 1 2 2 1 1 2 2
## ASV_2171 0 0 0 0 0 0 0 0
## ASV_3188 0 0 0 0 0 0 0 0
## ASV_2318 0 0 0 0 0 0 0 0
## ASV_4340 1 3 4 0 0 1 2 2
## ASV_5426 1 2 0 1 2 0 0 1
Although, 131 taxa could not be fit with the model this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type. See the feature table above.
## [1] 42
## [1] 67
There are 109 ASVs that have no reads in one sample type which is why they aren’t being fit to the model. Another 49 ASVs only have one read per sample type which will not allow them to be fit to the model.
## [1] "In feces, but not in grab samples"
## ASV_713
## "Firmicutes_Lachnospiraceae_Coprococcus_3"
## ASV_1393
## "Firmicutes_Lachnospiraceae_Cellulosilyticum"
## ASV_113
## "Firmicutes_Peptostreptococcaceae_Clostridioides"
## ASV_147
## "Firmicutes_Peptostreptococcaceae_Paeniclostridium"
## ASV_1336
## "Proteobacteria_Burkholderiaceae_Parasutterella"
## ASV_1247
## "Actinobacteria_Bifidobacteriaceae_Aeriscardovia"
## ASV_2770
## "Bacteroidetes_Marinifilaceae_Odoribacter"
## ASV_2544
## "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-011"
## ASV_1448
## "Firmicutes_Ruminococcaceae_Harryflintia"
## ASV_1756
## "Firmicutes_Ruminococcaceae_Negativibacillus"
## ASV_2759
## "Firmicutes_Ruminococcaceae_Pygmaiobacter"
## OTU Table: [1 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1393 0 0 0 0 0 0 0 0 0 0 0 0 7 19 14 5
## 370 371 372 373 374 375 376 378
## ASV_1393 4 14 26 7 7 5 7 2
## OTU Table: [1 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_113 0 0 0 0 0 0 0 0 0 0 0 0 33 31 32 47
## 370 371 372 373 374 375 376 378
## ASV_113 69 55 101 85 70 61 78 53
## OTU Table: [1 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1448 0 0 0 0 0 0 0 0 0 0 0 0 9 8 2 7
## 370 371 372 373 374 375 376 378
## ASV_1448 11 7 9 5 5 6 7 4
## [1] "In grab samples, but not in feces"
## ASV_429
## "Firmicutes_Lachnospiraceae_Acetatifactor"
## ASV_669
## "Firmicutes_Lachnospiraceae_Shuttleworthia"
## ASV_793
## "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006"
## ASV_456
## "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001"
## ASV_171
## "Proteobacteria_Succinivibrionaceae_Succinivibrio"
These ASVs couldn’t be fit to the model since there was zero reads in one sample type, but the other sample type has over 50 reads.
Let’s graph the one with the most reads ASV_113 Clostridioides.
Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:
There are 114 genera differentially abundant. We will look at the unique families they represent.
| Var1 | Freq |
|---|---|
| Firmicutes_Lachnospiraceae | 180 |
| Firmicutes_Ruminococcaceae | 156 |
| Firmicutes_Christensenellaceae | 105 |
| Firmicutes_Family_XIII | 30 |
| Bacteroidetes_Rikenellaceae | 24 |
| Bacteroidetes_Prevotellaceae | 19 |
| Euryarchaeota_Methanobacteriaceae | 13 |
| Firmicutes_Erysipelotrichaceae | 12 |
| Chloroflexi_Anaerolineaceae | 10 |
| Spirochaetes_Spirochaetaceae | 10 |
| Actinobacteria_Atopobiaceae | 9 |
| Tenericutes | 9 |
| Kiritimatiellaeota | 8 |
| Actinobacteria_Eggerthellaceae | 7 |
| Bacteroidetes_F082 | 6 |
| Fibrobacteres_Fibrobacteraceae | 6 |
| Bacteroidetes_Bacteroidales_BS11_gut_group | 3 |
| Firmicutes | 3 |
| Firmicutes_Defluviitaleaceae | 3 |
| Firmicutes_Peptococcaceae | 3 |
| Bacteroidetes | 2 |
| Bacteroidetes_Bacteroidaceae | 2 |
| Bacteroidetes_p-251-o5 | 2 |
| Firmicutes_Acidaminococcaceae | 2 |
| Firmicutes_Clostridiaceae_1 | 2 |
| Firmicutes_Eubacteriaceae | 2 |
| Firmicutes_Peptostreptococcaceae | 2 |
| Patescibacteria | 2 |
| Planctomycetes_Pirellulaceae | 2 |
| Proteobacteria | 2 |
| Proteobacteria_Desulfovibrionaceae | 2 |
| Proteobacteria_Succinivibrionaceae | 2 |
| Verrucomicrobia_Akkermansiaceae | 2 |
| Actinobacteria_Coriobacteriales_Incertae_Sedis | 1 |
| Bacteroidetes_Bacteroidales_RF16_group | 1 |
| Bacteroidetes_Marinilabiliaceae | 1 |
| Bacteroidetes_Muribaculaceae | 1 |
| Bacteroidetes_Tannerellaceae | 1 |
| Cyanobacteria | 1 |
| Elusimicrobia_Elusimicrobiaceae | 1 |
| Elusimicrobia_Endomicrobiaceae | 1 |
| Firmicutes_Lactobacillaceae | 1 |
| Firmicutes_Planococcaceae | 1 |
| Firmicutes_Streptococcaceae | 1 |
| Firmicutes_Veillonellaceae | 1 |
| Proteobacteria_Burkholderiaceae | 1 |
| Proteobacteria_Oligoflexaceae | 1 |
| Verrucomicrobia | 1 |
This graphs the ASVs in Bacteroidetes differentially abundantant. We do see that Rikenellaceae is lower in abundandance in feces compared grab samples, but we saw this was familiy was higher in relative abundance before so we will double check that.
| Sample_Type | Genus | mean | sd | sem | |
|---|---|---|---|---|---|
| 56 | Feces | Clostridioides | 0.6387915 | 0.1383558 | 0.0399399 |
| 181 | Feces | Paeniclostridium | 0.4938325 | 0.2294837 | 0.0662462 |
| 235 | Feces | Ruminococcaceae_UCG-005 | 0.2536037 | 0.7033963 | 0.0251856 |
| 76 | Feces | Dorea | 0.2388953 | 0.1933942 | 0.0394764 |
| 30 | Feces | Bacteroides | 0.2255830 | 0.2802845 | 0.0145321 |
| 223 | Feces | Romboutsia | 0.1954684 | 0.3827171 | 0.0390609 |
| 281 | Feces | Tyzzerella | 0.1555427 | 0.1656968 | 0.0276161 |
| 192 | Feces | Phascolarctobacterium | 0.1503569 | 0.0986420 | 0.0201352 |
| 204 | Feces | Prevotellaceae_UCG-004 | 0.1315314 | 0.3258646 | 0.0192018 |
| 280 | Feces | Turicibacter | 0.1190462 | 0.1990139 | 0.0287252 |
| 13 | Feces | Alistipes | 0.1151407 | 0.1833281 | 0.0085851 |
| 73 | Feces | dgA-11_gut_group | 0.0938341 | 0.1050319 | 0.0071465 |
| 11 | Feces | Agathobacter | 0.0848349 | 0.0697738 | 0.0116290 |
| 185 | Feces | Parasutterella | 0.0813552 | 0.0391629 | 0.0113053 |
| 109 | Feces | Harryflintia | 0.0789645 | 0.0457608 | 0.0132100 |
| 154 | Feces | Mailhella | 0.0741483 | 0.1563596 | 0.0170602 |
| 237 | Feces | Ruminococcaceae_UCG-009 | 0.0662564 | 0.0988824 | 0.0076289 |
| 12 | Feces | Akkermansia | 0.0600574 | 0.0750389 | 0.0046183 |
| 7 | Feces | Aeriscardovia | 0.0600208 | 0.0601411 | 0.0122762 |
| 169 | Feces | Negativibacillus | 0.0573690 | 0.0345288 | 0.0099676 |
| 116 | Feces | Incertae_Sedis | 0.0542774 | 0.0704945 | 0.0117491 |
| 23 | Feces | Anaerosporobacter | 0.0530864 | 0.0533739 | 0.0077039 |
| 94 | Feces | Flavonifractor | 0.0528531 | 0.0427194 | 0.0037182 |
| 283 | Feces | Tyzzerella_4 | 0.0467089 | 0.0498705 | 0.0058773 |
| 15 | Feces | Alloprevotella | 0.0453476 | 0.0862643 | 0.0071887 |
| 61 | Feces | Coprococcus_3 | 0.0437105 | 0.0564572 | 0.0057621 |
| 103 | Feces | GCA-900066225 | 0.0408701 | 0.0328104 | 0.0066974 |
| 126 | Feces | Lachnoclostridium | 0.0407673 | 0.0495309 | 0.0101105 |
| 241 | Feces | Ruminococcaceae_UCG-013 | 0.0395571 | 0.0572627 | 0.0018036 |
| 277 | Feces | Terrisporobacter | 0.0369988 | 0.0248179 | 0.0071643 |
| 44 | Feces | Candidatus_Soleaferrea | 0.0360129 | 0.0477317 | 0.0068895 |
| 222 | Feces | Rikenellaceae_RC9_gut_group | 0.0356341 | 0.0859706 | 0.0015986 |
| 160 | Feces | Methanocorpusculum | 0.0342023 | 0.0511104 | 0.0104329 |
| 186 | Feces | Parvibacter | 0.0335902 | 0.0291808 | 0.0084238 |
| 227 | Feces | Ruminiclostridium_5 | 0.0317005 | 0.0429588 | 0.0050627 |
| 178 | Feces | Oscillibacter | 0.0315691 | 0.0324547 | 0.0024190 |
| 89 | Feces | Family_XIII_AD3011_group | 0.0305030 | 0.0680737 | 0.0032306 |
| 234 | Feces | Ruminococcaceae_UCG-004 | 0.0304327 | 0.0652095 | 0.0084185 |
| 48 | Feces | Cellulosilyticum | 0.0297891 | 0.0569408 | 0.0082187 |
| 233 | Feces | Ruminococcaceae_UCG-002 | 0.0291055 | 0.0567230 | 0.0038595 |
| 239 | Feces | Ruminococcaceae_UCG-011 | 0.0263409 | 0.0228147 | 0.0038025 |
| 290 | Feces | XBB1006 | 0.0253367 | 0.0440793 | 0.0063623 |
| 108 | Feces | GWE2-31-10 | 0.0251856 | 0.0191693 | 0.0055337 |
| 238 | Feces | Ruminococcaceae_UCG-010 | 0.0248479 | 0.0461817 | 0.0008570 |
| 214 | Feces | Pygmaiobacter | 0.0245344 | 0.0192048 | 0.0039202 |
| 184 | Feces | Parabacteroides | 0.0241291 | 0.0298835 | 0.0060999 |
| 159 | Feces | Methanobrevibacter | 0.0236423 | 0.0618265 | 0.0037215 |
| 226 | Feces | Ruminiclostridium_1 | 0.0214905 | 0.0556286 | 0.0060696 |
| 225 | Feces | Ruminiclostridium | 0.0208239 | 0.0310066 | 0.0036542 |
| 285 | Feces | UBA1819 | 0.0193558 | 0.0156928 | 0.0045301 |
| 163 | Feces | Mogibacterium | 0.0193521 | 0.0581515 | 0.0040714 |
| 114 | Feces | Hydrogenoanaerobacterium | 0.0193362 | 0.0197852 | 0.0025543 |
| 174 | Feces | Odoribacter | 0.0192082 | 0.0235864 | 0.0039311 |
| 67 | Feces | Denitrobacterium | 0.0191882 | 0.0238792 | 0.0048743 |
| 3 | Feces | Acetobacter | 0.0185080 | 0.0204518 | 0.0041747 |
| 40 | Feces | Campylobacter | 0.0182729 | 0.0266641 | 0.0054428 |
| 57 | Feces | Clostridium_sensu_stricto_1 | 0.0164786 | 0.0278606 | 0.0030398 |
| 180 | Feces | p-1088-a5_gut_group | 0.0155396 | 0.0417214 | 0.0034768 |
| 229 | Feces | Ruminiclostridium_9 | 0.0150709 | 0.0267372 | 0.0023272 |
| 53 | Feces | Christensenellaceae_R-7_group | 0.0148646 | 0.0487342 | 0.0006503 |
| 203 | Feces | Prevotellaceae_UCG-003 | 0.0145027 | 0.0566721 | 0.0015390 |
| 231 | Feces | Ruminococcaceae_NK4A214_group | 0.0141766 | 0.0460014 | 0.0014076 |
| 113 | Feces | Hungatella | 0.0139791 | 0.0172950 | 0.0049926 |
| 10 | Feces | Aestuariispira | 0.0139554 | 0.0196823 | 0.0056818 |
| 117 | Feces | Intestinimonas | 0.0139085 | 0.0113642 | 0.0032806 |
| 133 | Feces | Lachnospiraceae_FCS020_group | 0.0138013 | 0.0401638 | 0.0032157 |
| 91 | Feces | FD2005 | 0.0135530 | 0.0265794 | 0.0038364 |
| 145 | Feces | Lachnospiraceae_UCG-010 | 0.0134737 | 0.0161588 | 0.0023323 |
| 151 | Feces | Lysinibacillus | 0.0134573 | 0.0148229 | 0.0042790 |
| 138 | Feces | Lachnospiraceae_NK4A136_group | 0.0107925 | 0.0262609 | 0.0015474 |
| 88 | Feces | Faecalibacterium | 0.0107498 | 0.0093950 | 0.0027121 |
| 79 | Feces | Elusimicrobium | 0.0107198 | 0.0256244 | 0.0024657 |
| 87 | Feces | Eubacterium | 0.0103994 | 0.0101764 | 0.0029377 |
| 137 | Feces | Lachnospiraceae_NK3A20_group | 0.0103956 | 0.0594491 | 0.0019816 |
| 293 | Feces | NA | 0.0103741 | 0.0392643 | 0.0002675 |
| 236 | Feces | Ruminococcaceae_UCG-007 | 0.0102813 | 0.0163617 | 0.0033398 |
| 45 | Feces | Caproiciproducens | 0.0102036 | 0.0142604 | 0.0023767 |
| 81 | Feces | Erysipelatoclostridium | 0.0101135 | 0.0147305 | 0.0024551 |
| 144 | Feces | Lachnospiraceae_UCG-009 | 0.0094588 | 0.0177503 | 0.0025620 |
| 224 | Feces | Roseburia | 0.0091183 | 0.0161287 | 0.0014723 |
| 59 | Feces | Coprococcus_1 | 0.0083048 | 0.0124823 | 0.0018017 |
| 2 | Feces | Acetitomaculum | 0.0082661 | 0.0252547 | 0.0010634 |
| 242 | Feces | Ruminococcaceae_UCG-014 | 0.0078948 | 0.0214008 | 0.0005786 |
| 60 | Feces | Coprococcus_2 | 0.0078869 | 0.0143832 | 0.0023972 |
| 217 | Feces | Raoultibacter | 0.0074416 | 0.0086101 | 0.0024855 |
| 90 | Feces | Family_XIII_UCG-001 | 0.0073221 | 0.0186402 | 0.0020338 |
| 36 | Feces | Breznakia | 0.0072076 | 0.0091047 | 0.0026283 |
| 96 | Feces | Fournierella | 0.0071908 | 0.0085943 | 0.0017543 |
| 74 | Feces | Dielma | 0.0071292 | 0.0083068 | 0.0023980 |
| 155 | Feces | Marvinbryantia | 0.0070862 | 0.0185011 | 0.0007962 |
| 86 | Feces | Escherichia/Shigella | 0.0069791 | 0.0095785 | 0.0027651 |
| 66 | Feces | Defluviitaleaceae_UCG-011 | 0.0069274 | 0.0173898 | 0.0015875 |
| 245 | Feces | Ruminococcus_2 | 0.0065609 | 0.0318101 | 0.0015748 |
| 176 | Feces | Olsenella | 0.0065356 | 0.0136794 | 0.0013163 |
| 37 | Feces | Butyrivibrio | 0.0063574 | 0.0117246 | 0.0023933 |
| 33 | Feces | Bilophila | 0.0061762 | 0.0106983 | 0.0030883 |
| 130 | Feces | Lachnoclostridium_5 | 0.0060615 | 0.0084681 | 0.0024445 |
| 202 | Feces | Prevotellaceae_UCG-001 | 0.0060065 | 0.0271684 | 0.0010575 |
| 171 | Feces | Nitrosomonas | 0.0059248 | 0.0102792 | 0.0029674 |
| 134 | Feces | Lachnospiraceae_FE2018_group | 0.0057836 | 0.0098037 | 0.0020012 |
| 25 | Feces | Anaerovorax | 0.0052314 | 0.0215634 | 0.0012706 |
| 50 | Feces | Cerasicoccus | 0.0048723 | 0.0101461 | 0.0029289 |
| 249 | Feces | Sanguibacteroides | 0.0048190 | 0.0065736 | 0.0018976 |
| 111 | Feces | hoa5-07d05_gut_group | 0.0048156 | 0.0097705 | 0.0028205 |
| 128 | Feces | Lachnoclostridium_10 | 0.0047588 | 0.0159617 | 0.0013893 |
| 200 | Feces | Prevotellaceae_Ga6A1_group | 0.0046212 | 0.0121785 | 0.0020297 |
| 75 | Feces | DNF00809 | 0.0045312 | 0.0099781 | 0.0006441 |
| 20 | Feces | Anaerofilum | 0.0042118 | 0.0070094 | 0.0020234 |
| 265 | Feces | Streptococcus | 0.0041349 | 0.0127466 | 0.0012265 |
| 161 | Feces | Methanosphaera | 0.0040941 | 0.0093743 | 0.0012102 |
| 34 | Feces | Blautia | 0.0038997 | 0.0121645 | 0.0007168 |
| 80 | Feces | Enterococcus | 0.0038507 | 0.0063274 | 0.0018265 |
| 255 | Feces | Sellimonas | 0.0036649 | 0.0079158 | 0.0016158 |
| 250 | Feces | Sarcina | 0.0036622 | 0.0097637 | 0.0028185 |
| 194 | Feces | Pirellula | 0.0036374 | 0.0069816 | 0.0020154 |
| 183 | Feces | Papillibacter | 0.0034728 | 0.0115269 | 0.0008893 |
| 282 | Feces | Tyzzerella_3 | 0.0034292 | 0.0128156 | 0.0011699 |
| 228 | Feces | Ruminiclostridium_6 | 0.0033738 | 0.0091114 | 0.0007593 |
| 147 | Feces | Lactobacillus | 0.0032990 | 0.0089522 | 0.0008614 |
| 83 | Feces | Erysipelotrichaceae_UCG-006 | 0.0032477 | 0.0074219 | 0.0015150 |
| 27 | Feces | Atopobium | 0.0027888 | 0.0079088 | 0.0006884 |
| 262 | Feces | Sporobacter | 0.0026935 | 0.0051575 | 0.0014888 |
| 21 | Feces | Anaerofustis | 0.0026664 | 0.0049651 | 0.0007167 |
| 64 | Feces | CPla-4_termite_group | 0.0025267 | 0.0074154 | 0.0015137 |
| 279 | Feces | Treponema_2 | 0.0024822 | 0.0156970 | 0.0004102 |
| 46 | Feces | Catenisphaera | 0.0023699 | 0.0043432 | 0.0012538 |
| 246 | Feces | Saccharofermentans | 0.0023208 | 0.0114662 | 0.0006620 |
| 173 | Feces | Ochrobactrum | 0.0022955 | 0.0042134 | 0.0012163 |
| 85 | Feces | Erysipelotrichaceae_UCG-009 | 0.0021437 | 0.0081140 | 0.0010475 |
| 244 | Feces | Ruminococcus_1 | 0.0021079 | 0.0089509 | 0.0002786 |
| 230 | Feces | Ruminobacter | 0.0019248 | 0.0062992 | 0.0010499 |
| 166 | Feces | Mucispirillum | 0.0018388 | 0.0063697 | 0.0018388 |
| 258 | Feces | Solobacterium | 0.0017884 | 0.0053905 | 0.0004921 |
| 170 | Feces | Neorhizobium | 0.0017712 | 0.0040531 | 0.0008273 |
| 141 | Feces | Lachnospiraceae_UCG-002 | 0.0017172 | 0.0054352 | 0.0004529 |
| 28 | Feces | Aurantimonas | 0.0015597 | 0.0037038 | 0.0010692 |
| 99 | Feces | Fusicatenibacter | 0.0015533 | 0.0053807 | 0.0015533 |
| 143 | Feces | Lachnospiraceae_UCG-008 | 0.0014649 | 0.0055222 | 0.0002657 |
| 100 | Feces | Fusobacterium | 0.0013048 | 0.0035323 | 0.0007210 |
| 292 | Feces | Z20 | 0.0012979 | 0.0044961 | 0.0012979 |
| 172 | Feces | Novosphingobium | 0.0012785 | 0.0044289 | 0.0012785 |
| 275 | Feces | Taibaiella | 0.0012785 | 0.0044289 | 0.0012785 |
| 43 | Feces | Candidatus_Saccharimonas | 0.0012466 | 0.0033976 | 0.0006935 |
| 112 | Feces | Howardella | 0.0012201 | 0.0049514 | 0.0006392 |
| 274 | Feces | Syntrophococcus | 0.0010753 | 0.0036596 | 0.0002728 |
| 271 | Feces | Sutterella | 0.0010377 | 0.0037369 | 0.0006228 |
| 195 | Feces | Planococcus | 0.0009107 | 0.0031549 | 0.0009107 |
| 32 | Feces | Bifidobacterium | 0.0008945 | 0.0030987 | 0.0008945 |
| 248 | Feces | Sanguibacter | 0.0008945 | 0.0030987 | 0.0008945 |
| 135 | Feces | Lachnospiraceae_NC2004_group | 0.0008615 | 0.0029843 | 0.0008615 |
| 95 | Feces | Flexilinea | 0.0008526 | 0.0036413 | 0.0001683 |
| 132 | Feces | Lachnospiraceae_AC2044_group | 0.0008081 | 0.0035506 | 0.0002237 |
| 5 | Feces | Actinobacillus | 0.0008044 | 0.0027864 | 0.0008044 |
| 17 | Feces | Alysiella | 0.0008044 | 0.0027864 | 0.0008044 |
| 125 | Feces | Kocuria | 0.0008044 | 0.0027864 | 0.0008044 |
| 157 | Feces | Megasphaera | 0.0008016 | 0.0027768 | 0.0008016 |
| 63 | Feces | Corynebacterium_1 | 0.0007743 | 0.0026185 | 0.0003779 |
| 198 | Feces | possible_genus_Sk018 | 0.0007410 | 0.0029886 | 0.0002876 |
| 52 | Feces | Chelatococcus | 0.0007272 | 0.0025190 | 0.0007272 |
| 14 | Feces | Allobaculum | 0.0006879 | 0.0023828 | 0.0006879 |
| 120 | Feces | Jeotgalicoccus | 0.0006879 | 0.0023828 | 0.0006879 |
| 263 | Feces | Staphylococcus | 0.0006879 | 0.0023828 | 0.0006879 |
| 266 | Feces | Subdoligranulum | 0.0006879 | 0.0023828 | 0.0006879 |
| 220 | Feces | Rhodococcus | 0.0006684 | 0.0022656 | 0.0004625 |
| 210 | Feces | Pseudochrobactrum | 0.0006490 | 0.0022481 | 0.0006490 |
| 211 | Feces | Pseudoclavibacter | 0.0006490 | 0.0022481 | 0.0006490 |
| 162 | Feces | Methylobacterium | 0.0006425 | 0.0028343 | 0.0004724 |
| 92 | Feces | Fibrobacter | 0.0004776 | 0.0035062 | 0.0001664 |
| 167 | Feces | Murdochiella | 0.0004597 | 0.0022520 | 0.0004597 |
| 82 | Feces | Erysipelotrichaceae_UCG-004 | 0.0004415 | 0.0029695 | 0.0001470 |
| 264 | Feces | Stenotrophomonas | 0.0004308 | 0.0021102 | 0.0004308 |
| 209 | Feces | Pseudobutyrivibrio | 0.0003630 | 0.0019076 | 0.0002081 |
| 22 | Feces | Anaeroplasma | 0.0003595 | 0.0025951 | 0.0001266 |
| 259 | Feces | Sphingobacterium | 0.0003065 | 0.0018388 | 0.0003065 |
| 140 | Feces | Lachnospiraceae_UCG-001 | 0.0002982 | 0.0017890 | 0.0002982 |
| 70 | Feces | Desulfovibrio | 0.0002802 | 0.0019098 | 0.0001473 |
| 243 | Feces | Ruminococcaceae_V9D2013_group | 0.0002605 | 0.0016139 | 0.0001292 |
| 165 | Feces | Moryella | 0.0002534 | 0.0019733 | 0.0001899 |
| 72 | Feces | Devosia | 0.0002293 | 0.0013757 | 0.0002293 |
| 97 | Feces | Fretibacterium | 0.0002293 | 0.0013757 | 0.0002293 |
| 146 | Feces | Lachnospiraceae_XPB1014_group | 0.0002248 | 0.0015558 | 0.0000864 |
| 115 | Feces | Hymenobacter | 0.0002163 | 0.0012979 | 0.0002163 |
| 253 | Feces | Selenomonas_1 | 0.0002131 | 0.0018081 | 0.0002131 |
| 24 | Feces | Anaerovibrio | 0.0001839 | 0.0014243 | 0.0001839 |
| 188 | Feces | Pedobacter | 0.0001839 | 0.0014243 | 0.0001839 |
| 136 | Feces | Lachnospiraceae_ND3007_group | 0.0001800 | 0.0016394 | 0.0000946 |
| 270 | Feces | Succinivibrionaceae_UCG-002 | 0.0001723 | 0.0013346 | 0.0001723 |
| 41 | Feces | Candidatus_Endomicrobium | 0.0001518 | 0.0012880 | 0.0001518 |
| 201 | Feces | Prevotellaceae_NK3B31_group | 0.0000944 | 0.0009800 | 0.0000667 |
| 206 | Feces | probable_genus_10 | 0.0000913 | 0.0011837 | 0.0000913 |
| 38 | Feces | Butyrivibrio_2 | 0.0000912 | 0.0010955 | 0.0000482 |
| 212 | Feces | Pseudomonas | 0.0000862 | 0.0009437 | 0.0000862 |
| 267 | Feces | Succiniclasticum | 0.0000813 | 0.0009343 | 0.0000813 |
| 177 | Feces | Oribacterium | 0.0000536 | 0.0007652 | 0.0000536 |
| 199 | Feces | Prevotella_1 | 0.0000325 | 0.0006350 | 0.0000104 |
| 1 | Feces | Acetatifactor | 0.0000000 | 0.0000000 | 0.0000000 |
| 4 | Feces | Acinetobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 6 | Feces | Aeribacillus | 0.0000000 | 0.0000000 | 0.0000000 |
| 8 | Feces | Aerococcus | 0.0000000 | 0.0000000 | 0.0000000 |
| 9 | Feces | Aeromicrobium | 0.0000000 | 0.0000000 | 0.0000000 |
| 16 | Feces | Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium | 0.0000000 | 0.0000000 | 0.0000000 |
| 18 | Feces | Anaerobiospirillum | 0.0000000 | 0.0000000 | 0.0000000 |
| 19 | Feces | Anaerocella | 0.0000000 | 0.0000000 | 0.0000000 |
| 26 | Feces | Angelakisella | 0.0000000 | 0.0000000 | 0.0000000 |
| 29 | Feces | Aureimonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 31 | Feces | Bibersteinia | 0.0000000 | 0.0000000 | 0.0000000 |
| 35 | Feces | Brevundimonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 39 | Feces | CAG-352 | 0.0000000 | 0.0000000 | 0.0000000 |
| 42 | Feces | Candidatus_Methanomethylophilus | 0.0000000 | 0.0000000 | 0.0000000 |
| 47 | Feces | Caviibacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 49 | Feces | Cellvibrio | 0.0000000 | 0.0000000 | 0.0000000 |
| 51 | Feces | Chelativorans | 0.0000000 | 0.0000000 | 0.0000000 |
| 54 | Feces | Chryseobacterium | 0.0000000 | 0.0000000 | 0.0000000 |
| 55 | Feces | Clavibacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 58 | Feces | Comamonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 62 | Feces | Corynebacterium | 0.0000000 | 0.0000000 | 0.0000000 |
| 65 | Feces | Curtobacterium | 0.0000000 | 0.0000000 | 0.0000000 |
| 68 | Feces | Desemzia | 0.0000000 | 0.0000000 | 0.0000000 |
| 69 | Feces | Desulfobulbus | 0.0000000 | 0.0000000 | 0.0000000 |
| 71 | Feces | Desulfuromonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 77 | Feces | Duganella | 0.0000000 | 0.0000000 | 0.0000000 |
| 78 | Feces | Dyadobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 84 | Feces | Erysipelotrichaceae_UCG-008 | 0.0000000 | 0.0000000 | 0.0000000 |
| 93 | Feces | Filifactor | 0.0000000 | 0.0000000 | 0.0000000 |
| 98 | Feces | Frigoribacterium | 0.0000000 | 0.0000000 | 0.0000000 |
| 101 | Feces | Galbitalea | 0.0000000 | 0.0000000 | 0.0000000 |
| 102 | Feces | Gallicola | 0.0000000 | 0.0000000 | 0.0000000 |
| 104 | Feces | GCA-900066575 | 0.0000000 | 0.0000000 | 0.0000000 |
| 105 | Feces | Gillisia | 0.0000000 | 0.0000000 | 0.0000000 |
| 106 | Feces | Gilvimarinus | 0.0000000 | 0.0000000 | 0.0000000 |
| 107 | Feces | Glutamicibacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 110 | Feces | Helcococcus | 0.0000000 | 0.0000000 | 0.0000000 |
| 118 | Feces | Janthinobacterium | 0.0000000 | 0.0000000 | 0.0000000 |
| 119 | Feces | Jeotgalibaca | 0.0000000 | 0.0000000 | 0.0000000 |
| 121 | Feces | Kandleria | 0.0000000 | 0.0000000 | 0.0000000 |
| 122 | Feces | Ketogulonicigenium | 0.0000000 | 0.0000000 | 0.0000000 |
| 123 | Feces | Kineococcus | 0.0000000 | 0.0000000 | 0.0000000 |
| 124 | Feces | Klebsiella | 0.0000000 | 0.0000000 | 0.0000000 |
| 127 | Feces | Lachnoclostridium_1 | 0.0000000 | 0.0000000 | 0.0000000 |
| 129 | Feces | Lachnoclostridium_12 | 0.0000000 | 0.0000000 | 0.0000000 |
| 131 | Feces | Lachnospira | 0.0000000 | 0.0000000 | 0.0000000 |
| 139 | Feces | Lachnospiraceae_NK4B4_group | 0.0000000 | 0.0000000 | 0.0000000 |
| 142 | Feces | Lachnospiraceae_UCG-006 | 0.0000000 | 0.0000000 | 0.0000000 |
| 148 | Feces | Leptotrichia | 0.0000000 | 0.0000000 | 0.0000000 |
| 149 | Feces | Leucobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 150 | Feces | Limnohabitans | 0.0000000 | 0.0000000 | 0.0000000 |
| 152 | Feces | M2PT2-76_termite_group | 0.0000000 | 0.0000000 | 0.0000000 |
| 153 | Feces | Macellibacteroides | 0.0000000 | 0.0000000 | 0.0000000 |
| 156 | Feces | Massilia | 0.0000000 | 0.0000000 | 0.0000000 |
| 158 | Feces | Methanimicrococcus | 0.0000000 | 0.0000000 | 0.0000000 |
| 164 | Feces | Moraxella | 0.0000000 | 0.0000000 | 0.0000000 |
| 168 | Feces | Mycoplasma | 0.0000000 | 0.0000000 | 0.0000000 |
| 175 | Feces | Oligella | 0.0000000 | 0.0000000 | 0.0000000 |
| 179 | Feces | Oscillospira | 0.0000000 | 0.0000000 | 0.0000000 |
| 182 | Feces | Pantoea | 0.0000000 | 0.0000000 | 0.0000000 |
| 187 | Feces | Parvimonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 189 | Feces | Pelospora | 0.0000000 | 0.0000000 | 0.0000000 |
| 190 | Feces | Peptococcus | 0.0000000 | 0.0000000 | 0.0000000 |
| 191 | Feces | Peptoniphilus | 0.0000000 | 0.0000000 | 0.0000000 |
| 193 | Feces | Pigmentiphaga | 0.0000000 | 0.0000000 | 0.0000000 |
| 196 | Feces | Pontibacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 197 | Feces | Porphyromonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 205 | Feces | Prevotellaceae_YAB2003_group | 0.0000000 | 0.0000000 | 0.0000000 |
| 207 | Feces | Proteiniclasticum | 0.0000000 | 0.0000000 | 0.0000000 |
| 208 | Feces | Proteiniphilum | 0.0000000 | 0.0000000 | 0.0000000 |
| 213 | Feces | Psychrobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 215 | Feces | Pyramidobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 216 | Feces | Quinella | 0.0000000 | 0.0000000 | 0.0000000 |
| 218 | Feces | Rathayibacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 219 | Feces | Rhodobacter | 0.0000000 | 0.0000000 | 0.0000000 |
| 221 | Feces | Rikenella | 0.0000000 | 0.0000000 | 0.0000000 |
| 232 | Feces | Ruminococcaceae_UCG-001 | 0.0000000 | 0.0000000 | 0.0000000 |
| 240 | Feces | Ruminococcaceae_UCG-012 | 0.0000000 | 0.0000000 | 0.0000000 |
| 247 | Feces | Salana | 0.0000000 | 0.0000000 | 0.0000000 |
| 251 | Feces | Schwartzia | 0.0000000 | 0.0000000 | 0.0000000 |
| 252 | Feces | Sediminispirochaeta | 0.0000000 | 0.0000000 | 0.0000000 |
| 254 | Feces | Selenomonas_4 | 0.0000000 | 0.0000000 | 0.0000000 |
| 256 | Feces | Shuttleworthia | 0.0000000 | 0.0000000 | 0.0000000 |
| 257 | Feces | Slackia | 0.0000000 | 0.0000000 | 0.0000000 |
| 260 | Feces | Sphingobium | 0.0000000 | 0.0000000 | 0.0000000 |
| 261 | Feces | Sphingomonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 268 | Feces | Succinimonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 269 | Feces | Succinivibrio | 0.0000000 | 0.0000000 | 0.0000000 |
| 272 | Feces | Suttonella | 0.0000000 | 0.0000000 | 0.0000000 |
| 273 | Feces | Synergistes | 0.0000000 | 0.0000000 | 0.0000000 |
| 276 | Feces | Tannerella | 0.0000000 | 0.0000000 | 0.0000000 |
| 278 | Feces | Thermomonas | 0.0000000 | 0.0000000 | 0.0000000 |
| 284 | Feces | U29-B03 | 0.0000000 | 0.0000000 | 0.0000000 |
| 286 | Feces | Variovorax | 0.0000000 | 0.0000000 | 0.0000000 |
| 287 | Feces | Veillonellaceae_UCG-001 | 0.0000000 | 0.0000000 | 0.0000000 |
| 288 | Feces | Verticia | 0.0000000 | 0.0000000 | 0.0000000 |
| 289 | Feces | Weissella | 0.0000000 | 0.0000000 | 0.0000000 |
| 291 | Feces | Xylophilus | 0.0000000 | 0.0000000 | 0.0000000 |
| Sample_Type | Genus | mean | sd | sem | |
|---|---|---|---|---|---|
| 9 | Feces | Alistipes | 0.1151407 | 0.1833281 | 0.0085851 |
| 11 | Feces | dgA-11_gut_group | 0.0938341 | 0.1050319 | 0.0071465 |
| 14 | Feces | Rikenellaceae_RC9_gut_group | 0.0356341 | 0.0859706 | 0.0015986 |
| 16 | Feces | NA | 0.0321720 | 0.0516502 | 0.0066680 |
| 38 | Solid | Rikenellaceae_RC9_gut_group | 0.0305544 | 0.0893249 | 0.0016610 |
| 6 | Grab Sample | Rikenellaceae_RC9_gut_group | 0.0293962 | 0.0865592 | 0.0016096 |
| 22 | Stomach Tube | Rikenellaceae_RC9_gut_group | 0.0287573 | 0.0782038 | 0.0014542 |
| 46 | Liquid Unstrained | Rikenellaceae_RC9_gut_group | 0.0240750 | 0.0592204 | 0.0013487 |
| 39 | Solid | U29-B03 | 0.0202607 | 0.0140115 | 0.0028601 |
| 30 | Liquid Strained | Rikenellaceae_RC9_gut_group | 0.0195953 | 0.0571284 | 0.0010623 |
| 7 | Grab Sample | U29-B03 | 0.0176858 | 0.0225679 | 0.0046067 |
| 23 | Stomach Tube | U29-B03 | 0.0087306 | 0.0104589 | 0.0021349 |
| 47 | Liquid Unstrained | U29-B03 | 0.0079824 | 0.0112709 | 0.0028177 |
| 12 | Feces | hoa5-07d05_gut_group | 0.0048156 | 0.0097705 | 0.0028205 |
| 44 | Liquid Unstrained | hoa5-07d05_gut_group | 0.0040984 | 0.0076867 | 0.0027177 |
| 31 | Liquid Strained | U29-B03 | 0.0040380 | 0.0078627 | 0.0016050 |
| 4 | Grab Sample | hoa5-07d05_gut_group | 0.0032071 | 0.0077284 | 0.0022310 |
| 32 | Liquid Strained | NA | 0.0017208 | 0.0065606 | 0.0008470 |
| 28 | Liquid Strained | hoa5-07d05_gut_group | 0.0015568 | 0.0042730 | 0.0012335 |
| 40 | Solid | NA | 0.0015567 | 0.0064352 | 0.0008308 |
| 48 | Liquid Unstrained | NA | 0.0015525 | 0.0054636 | 0.0008639 |
| 5 | Grab Sample | Rikenella | 0.0014625 | 0.0050663 | 0.0014625 |
| 42 | Liquid Unstrained | Anaerocella | 0.0012392 | 0.0035050 | 0.0012392 |
| 24 | Stomach Tube | NA | 0.0012366 | 0.0054721 | 0.0007064 |
| 20 | Stomach Tube | hoa5-07d05_gut_group | 0.0012348 | 0.0042773 | 0.0012348 |
| 45 | Liquid Unstrained | Rikenella | 0.0009321 | 0.0026365 | 0.0009321 |
| 26 | Liquid Strained | Anaerocella | 0.0007805 | 0.0027037 | 0.0007805 |
| 8 | Grab Sample | NA | 0.0007000 | 0.0038342 | 0.0004950 |
| 37 | Solid | Rikenella | 0.0006256 | 0.0021671 | 0.0006256 |
| 41 | Liquid Unstrained | Alistipes | 0.0003632 | 0.0023145 | 0.0001327 |
| 43 | Liquid Unstrained | dgA-11_gut_group | 0.0002380 | 0.0017008 | 0.0001417 |
| 17 | Stomach Tube | Alistipes | 0.0002040 | 0.0018299 | 0.0000857 |
| 25 | Liquid Strained | Alistipes | 0.0001770 | 0.0011256 | 0.0000527 |
| 1 | Grab Sample | Alistipes | 0.0001556 | 0.0016626 | 0.0000779 |
| 35 | Solid | dgA-11_gut_group | 0.0001345 | 0.0011416 | 0.0000777 |
| 27 | Liquid Strained | dgA-11_gut_group | 0.0001136 | 0.0010386 | 0.0000707 |
| 33 | Solid | Alistipes | 0.0000872 | 0.0009282 | 0.0000435 |
| 3 | Grab Sample | dgA-11_gut_group | 0.0000813 | 0.0011941 | 0.0000813 |
| 19 | Stomach Tube | dgA-11_gut_group | 0.0000686 | 0.0010082 | 0.0000686 |
| 2 | Grab Sample | Anaerocella | 0.0000000 | 0.0000000 | 0.0000000 |
| 10 | Feces | Anaerocella | 0.0000000 | 0.0000000 | 0.0000000 |
| 13 | Feces | Rikenella | 0.0000000 | 0.0000000 | 0.0000000 |
| 15 | Feces | U29-B03 | 0.0000000 | 0.0000000 | 0.0000000 |
| 18 | Stomach Tube | Anaerocella | 0.0000000 | 0.0000000 | 0.0000000 |
| 21 | Stomach Tube | Rikenella | 0.0000000 | 0.0000000 | 0.0000000 |
| 29 | Liquid Strained | Rikenella | 0.0000000 | 0.0000000 | 0.0000000 |
| 34 | Solid | Anaerocella | 0.0000000 | 0.0000000 | 0.0000000 |
| 36 | Solid | hoa5-07d05_gut_group | 0.0000000 | 0.0000000 | 0.0000000 |
From these graphs we can see that Rikenellaceae_RC9_gut_group appears to be higher in feces there is also other genera (Alistipes,dgA_11_gut_group) in the Rikenellaceae family that cause the overall relative abundance of this family to be higher than in grab samples. However, there are certain ASVs in Rikenellaceae that are significantly lower in feces. This backs up the corncob data.
Genera in Firmicutes differentially abundantant between feces and grab samples.
| Var1 | Freq |
|---|---|
| Firmicutes | 504 |
| Bacteroidetes | 62 |
| Actinobacteria | 17 |
| Euryarchaeota | 13 |
| Chloroflexi | 10 |
| Spirochaetes | 10 |
| Tenericutes | 9 |
| Kiritimatiellaeota | 8 |
| Proteobacteria | 8 |
| Fibrobacteres | 6 |
| Verrucomicrobia | 3 |
| Elusimicrobia | 2 |
| Patescibacteria | 2 |
| Planctomycetes | 2 |
| Cyanobacteria | 1 |
While the most common phyla to have significant differentially abundant taxa were Firmicutes and Bacteroidetes this could be because they are the most dominant taxa rather than really being “more important” in distinguishing sample types.
| Phylum | #Significant ASVs | Total ASVs | Percent Significant ASVs |
|---|---|---|---|
| Actinobacteria | 17 | 96 | 17.708333 |
| Bacteroidetes | 62 | 1257 | 4.932379 |
| Chloroflexi | 10 | 39 | 25.641026 |
| Cyanobacteria | 1 | 65 | 1.538461 |
| Elusimicrobia | 2 | 16 | 12.500000 |
| Euryarchaeota | 13 | 44 | 29.545455 |
| Fibrobacteres | 6 | 39 | 15.384615 |
| Firmicutes | 504 | 3095 | 16.284330 |
| Kiritimatiellaeota | 8 | 180 | 4.444444 |
| Patescibacteria | 2 | 14 | 14.285714 |
| Planctomycetes | 2 | 15 | 13.333333 |
| Proteobacteria | 8 | 219 | 3.652968 |
| Spirochaetes | 10 | 138 | 7.246377 |
| Tenericutes | 9 | 188 | 4.787234 |
| Verrucomicrobia | 3 | 35 | 8.571429 |
| Deferribacteres | 0 | 1 | 0.000000 |
| Epsilonbacteraeota | 0 | 2 | 0.000000 |
| Fusobacteria | 0 | 4 | 0.000000 |
| Gemmatimonadetes | 0 | 1 | 0.000000 |
| Lentisphaerae | 0 | 31 | 0.000000 |
| Synergistetes | 0 | 6 | 0.000000 |
This table shows that while Firmicutes and Bacteroidetes are the most common phyla to have differentially abundant taxa this is in part due the fact that they are the most prevelant phyla. As a percent Chloroflexi and Euryarcheota are more common.
We will graph out the significantly different taxa from these phylums.
Here we can see that the Euryarchaeota that are important for telling samples types apart are all methogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.
## [1] "Flexilinea"
## OTU Table: [38 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3963 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1206 2 0 2 1 1 6 0 0 0 0 0 2 0 0 0 0
## ASV_1519 0 1 0 3 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_1003 2 1 1 2 2 1 2 2 1 1 2 2 0 0 0 0
## ASV_3326 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0
## ASV_1572 0 0 3 2 2 3 2 0 3 0 0 0 0 0 0 0
## ASV_1315 1 0 1 1 1 3 1 1 2 0 0 0 0 0 1 0
## ASV_3266 0 2 1 0 2 1 0 0 0 0 1 0 0 0 0 0
## ASV_727 2 0 3 2 0 4 4 1 1 3 2 4 0 1 0 0
## ASV_2479 0 0 0 0 3 0 0 1 1 0 0 2 0 1 0 0
## ASV_1570 1 0 0 1 2 1 0 0 2 0 2 0 0 0 0 1
## ASV_1257 0 0 0 1 1 0 1 0 2 0 0 0 0 0 0 0
## ASV_1826 1 1 0 2 0 2 0 1 0 0 1 0 0 0 0 0
## ASV_4222 0 2 0 1 0 0 0 0 0 1 0 0 0 0 0 0
## ASV_612 1 1 1 3 1 3 0 1 2 0 2 1 0 0 0 1
## ASV_2625 1 0 0 0 0 0 1 1 1 2 0 0 0 0 0 0
## ASV_3203 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_2739 3 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0
## ASV_3861 0 0 0 1 0 0 1 2 1 0 0 0 0 0 0 0
## ASV_3258 0 0 0 6 2 1 0 0 0 0 0 0 0 0 0 0
## ASV_2612 0 2 0 4 0 0 0 0 0 1 1 0 0 0 0 0
## ASV_1761 0 0 1 2 0 1 0 0 1 0 1 1 0 0 0 0
## ASV_2122 0 1 0 2 1 1 0 1 1 0 1 1 0 0 0 0
## ASV_1879 0 0 0 1 2 0 2 3 1 0 5 0 0 0 0 0
## ASV_2100 0 2 2 1 0 1 1 1 0 1 1 0 0 0 1 0
## ASV_409 6 4 4 8 3 7 8 2 5 3 3 2 0 0 0 0
## ASV_4093 0 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0
## ASV_2353 0 0 0 1 0 0 1 0 1 1 0 4 0 0 0 0
## ASV_594 2 1 2 3 1 2 6 3 3 6 6 7 2 0 1 0
## ASV_2831 0 1 0 0 0 0 0 1 0 0 2 1 0 0 0 0
## ASV_743 2 0 1 2 0 1 6 5 6 1 2 2 0 0 0 0
## ASV_1877 0 1 0 0 0 1 1 1 1 0 1 0 0 0 0 0
## ASV_1428 2 3 0 0 1 1 2 4 0 0 0 0 0 1 0 0
## ASV_1620 1 1 1 2 1 2 1 2 0 1 1 1 0 0 0 0
## ASV_4680 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0
## ASV_2984 3 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0
## ASV_3303 0 2 0 1 1 0 0 0 0 0 2 1 0 0 0 0
## ASV_3402 0 0 0 2 1 1 0 0 0 1 2 0 0 0 0 0
## 370 371 372 373 374 375 376 378
## ASV_3963 0 0 0 0 1 0 0 0
## ASV_1206 0 2 0 0 0 0 0 0
## ASV_1519 0 1 0 0 0 0 1 0
## ASV_1003 0 0 1 0 0 0 0 0
## ASV_3326 0 0 0 0 0 0 0 0
## ASV_1572 0 0 0 0 0 0 0 0
## ASV_1315 0 0 0 0 0 0 1 0
## ASV_3266 0 0 0 1 0 0 0 0
## ASV_727 2 0 1 1 1 1 0 0
## ASV_2479 0 0 0 0 0 0 0 0
## ASV_1570 0 0 0 0 0 0 0 0
## ASV_1257 0 0 0 0 0 0 0 0
## ASV_1826 0 0 0 0 0 0 0 0
## ASV_4222 0 0 0 0 0 0 0 0
## ASV_612 1 0 0 0 0 0 0 0
## ASV_2625 0 0 0 0 0 0 0 0
## ASV_3203 0 0 0 0 0 0 0 0
## ASV_2739 0 0 0 0 0 1 0 0
## ASV_3861 0 0 0 0 0 0 0 0
## ASV_3258 0 0 0 0 0 0 0 0
## ASV_2612 0 0 0 0 0 0 0 0
## ASV_1761 1 0 0 0 0 0 0 0
## ASV_2122 0 0 0 0 0 0 0 0
## ASV_1879 0 0 0 1 1 0 0 0
## ASV_2100 0 0 0 0 0 0 0 2
## ASV_409 0 0 0 0 0 0 0 1
## ASV_4093 0 0 0 0 0 0 0 0
## ASV_2353 0 0 0 0 0 0 0 0
## ASV_594 0 0 0 0 1 0 0 0
## ASV_2831 0 0 0 0 0 0 0 0
## ASV_743 0 0 0 0 0 0 0 0
## ASV_1877 0 1 0 0 0 0 0 0
## ASV_1428 0 0 0 0 0 0 0 0
## ASV_1620 0 0 0 0 0 0 0 0
## ASV_4680 0 0 0 0 0 0 0 0
## ASV_2984 0 0 0 0 0 0 0 0
## ASV_3303 0 0 0 0 0 0 0 0
## ASV_3402 0 0 0 0 0 0 0 0
## [1] 20
Flexilinea is the only Genus found in the phylum Chloroflexi in this data set. It also seems like there are a number of ASVs that don’t have an reads in fecal samples. Let’s look at the ASV level.
We will look into Euryarchaeota ASVs a bit more now.
## [1] 12
## ASV_1308
## "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter"
## ASV_3184
## "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera"
## ASV_484
## "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter"
## ASV_3936
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus"
## ASV_231
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_3478
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_657
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_2010
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_2978
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_2521
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_3242
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## ASV_3537
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## OTU Table: [12 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3936 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_231 13 3 1 5 7 3 8 15 7 3 4 5 0 0 0 0
## ASV_3478 1 1 0 0 0 1 0 0 0 1 1 0 0 0 0 0
## ASV_657 1 0 0 1 1 1 2 1 3 0 3 0 0 0 0 0
## ASV_2010 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1584 0 0 0 0 0 0 4 0 0 0 0 0 0 0 2 0
## ASV_2978 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1603 0 2 1 0 1 2 0 0 0 0 1 0 0 0 0 0
## ASV_2521 0 0 1 0 0 0 1 0 0 2 0 0 0 0 0 0
## ASV_3242 1 0 1 1 0 0 1 0 0 0 1 1 0 0 0 0
## ASV_3537 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0
## ASV_3875 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## 370 371 372 373 374 375 376 378
## ASV_3936 0 0 0 0 0 0 0 0
## ASV_231 0 0 0 0 0 0 0 0
## ASV_3478 0 0 0 0 0 0 0 0
## ASV_657 0 0 0 0 0 0 0 0
## ASV_2010 0 0 0 0 0 0 0 0
## ASV_1584 0 0 0 0 0 0 0 0
## ASV_2978 0 0 0 0 0 0 0 0
## ASV_1603 0 1 0 0 0 0 0 0
## ASV_2521 0 0 0 0 0 0 0 0
## ASV_3242 0 0 0 0 0 0 0 0
## ASV_3537 0 0 0 0 0 0 0 0
## ASV_3875 0 0 0 1 0 0 0 0
## OTU Table: [2 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1434 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 18
## ASV_4298 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## 370 371 372 373 374 375 376 378
## ASV_1434 3 5 4 5 5 9 7 21
## ASV_4298 0 1 2 0 1 0 0 0
There are increased amounts of Methanocorpusculum in one ASV, but the other ASV has low amounts so it seems like not a strong enough association to bring this up.
Based on the DPCoA the phyla Spirochaetes and Actinobacteria also play and important role in distinguishing feces from grab samples.
| Var1 | Freq |
|---|---|
| Firmicutes_Lachnospiraceae | 32 |
| Firmicutes_Ruminococcaceae | 23 |
| Bacteroidetes_Prevotellaceae | 7 |
| Firmicutes_Erysipelotrichaceae | 7 |
| Firmicutes_Family_XIII | 4 |
| Bacteroidetes_Rikenellaceae | 3 |
| Actinobacteria_Atopobiaceae | 2 |
| Actinobacteria_Eggerthellaceae | 2 |
| Euryarchaeota_Methanobacteriaceae | 2 |
| Firmicutes_Acidaminococcaceae | 2 |
| Firmicutes_Veillonellaceae | 2 |
| Planctomycetes_Pirellulaceae | 2 |
| Proteobacteria_Desulfovibrionaceae | 2 |
| Proteobacteria_Succinivibrionaceae | 2 |
| Actinobacteria_Coriobacteriales_Incertae_Sedis | 1 |
| Actinobacteria_Corynebacteriaceae | 1 |
| Bacteroidetes_Bacteroidaceae | 1 |
| Bacteroidetes_Tannerellaceae | 1 |
| Chloroflexi_Anaerolineaceae | 1 |
| Elusimicrobia_Elusimicrobiaceae | 1 |
| Elusimicrobia_Endomicrobiaceae | 1 |
| Epsilonbacteraeota_Campylobacteraceae | 1 |
| Euryarchaeota_Methanocorpusculaceae | 1 |
| Fibrobacteres_Fibrobacteraceae | 1 |
| Firmicutes_Christensenellaceae | 1 |
| Firmicutes_Clostridiaceae_1 | 1 |
| Firmicutes_Defluviitaleaceae | 1 |
| Firmicutes_Eubacteriaceae | 1 |
| Firmicutes_Peptostreptococcaceae | 1 |
| Firmicutes_Streptococcaceae | 1 |
| Proteobacteria_Burkholderiaceae | 1 |
| Proteobacteria_Devosiaceae | 1 |
| Spirochaetes_Spirochaetaceae | 1 |
| Synergistetes_Synergistaceae | 1 |
| Tenericutes_Anaeroplasmataceae | 1 |
| Verrucomicrobia_Akkermansiaceae | 1 |
From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to be differentially abundant in feces compared to grab samples. We will take a closer look at all ASVs differentially abundant.
| p_value | ASV | Taxa | |
|---|---|---|---|
| 1 | 1.51e-03 | ASV_1 | Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group |
| 2 | 1.51e-03 | ASV_10 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans |
| 3 | 1.51e-03 | ASV_1006 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea |
| 4 | 1.51e-03 | ASV_1014 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax |
| 5 | 1.51e-03 | ASV_1016 | Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis |
| 6 | 1.51e-03 | ASV_103 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1 |
| 7 | 1.51e-03 | ASV_105 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group |
| 8 | 1.51e-03 | ASV_1098 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014 |
| 10 | 1.51e-03 | ASV_1118 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4 |
| 11 | 1.51e-03 | ASV_1130 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018 |
| 12 | 1.51e-03 | ASV_1132 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group |
| 13 | 1.51e-03 | ASV_1169 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus |
| 15 | 1.51e-03 | ASV_1220 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5 |
| 16 | 1.51e-03 | ASV_1221 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium |
| 17 | 1.51e-03 | ASV_124 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group |
| 18 | 1.51e-03 | ASV_1256 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group |
| 20 | 1.51e-03 | ASV_13 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group |
| 21 | 1.51e-03 | ASV_1325 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009 |
| 23 | 1.51e-03 | ASV_14 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium |
| 25 | 1.51e-03 | ASV_149 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio |
| 26 | 1.51e-03 | ASV_1563 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium |
| 28 | 1.51e-03 | ASV_168 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter |
| 29 | 1.51e-03 | ASV_1682 | Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1 |
| 30 | 1.51e-03 | ASV_1688 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_GCA-900066225 |
| 31 | 1.51e-03 | ASV_172 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809 |
| 32 | 1.51e-03 | ASV_184 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera |
| 33 | 1.51e-03 | ASV_1882 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia |
| 35 | 1.51e-03 | ASV_199 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella |
| 36 | 1.51e-03 | ASV_2 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group |
| 37 | 1.51e-03 | ASV_201 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group |
| 38 | 1.51e-03 | ASV_204 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Dorea |
| 41 | 1.51e-03 | ASV_210 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10 |
| 42 | 1.51e-03 | ASV_2189 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001 |
| 43 | 1.51e-03 | ASV_22 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella |
| 46 | 1.51e-03 | ASV_227 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella |
| 47 | 1.51e-03 | ASV_23 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1 |
| 50 | 1.51e-03 | ASV_235 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1 |
| 52 | 1.51e-03 | ASV_246 | Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma |
| 53 | 1.51e-03 | ASV_247 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009 |
| 54 | 1.51e-03 | ASV_25 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio |
| 55 | 1.51e-03 | ASV_254 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010 |
| 57 | 1.51e-03 | ASV_26 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004 |
| 58 | 1.51e-03 | ASV_267 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013 |
| 60 | 1.51e-03 | ASV_3 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005 |
| 61 | 1.51e-03 | ASV_3005 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Hydrogenoanaerobacterium |
| 63 | 1.51e-03 | ASV_311 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella |
| 64 | 1.51e-03 | ASV_320 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10 |
| 65 | 1.51e-03 | ASV_330 | Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia |
| 66 | 1.51e-03 | ASV_335 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group |
| 67 | 1.51e-03 | ASV_344 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group |
| 68 | 1.51e-03 | ASV_348 | Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011 |
| 69 | 1.51e-03 | ASV_357 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002 |
| 70 | 1.51e-03 | ASV_36 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides |
| 71 | 1.51e-03 | ASV_37 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter |
| 73 | 1.51e-03 | ASV_376 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group |
| 77 | 1.51e-03 | ASV_409 | Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea |
| 78 | 1.51e-03 | ASV_418 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium |
| 79 | 1.51e-03 | ASV_442 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium |
| 81 | 1.51e-03 | ASV_457 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008 |
| 82 | 1.51e-03 | ASV_471 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium |
| 83 | 1.51e-03 | ASV_48 | Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia |
| 84 | 1.51e-03 | ASV_510 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella |
| 85 | 1.51e-03 | ASV_52 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1 |
| 86 | 1.51e-03 | ASV_524 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002 |
| 88 | 1.51e-03 | ASV_560 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6 |
| 90 | 1.51e-03 | ASV_57 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia |
| 91 | 1.51e-03 | ASV_60 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes |
| 92 | 1.51e-03 | ASV_601 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009 |
| 93 | 1.51e-03 | ASV_622 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium |
| 94 | 1.51e-03 | ASV_656 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter |
| 96 | 1.51e-03 | ASV_674 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera |
| 97 | 1.51e-03 | ASV_68 | Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter |
| 98 | 1.51e-03 | ASV_7 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter |
| 99 | 1.51e-03 | ASV_71 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2 |
| 100 | 1.51e-03 | ASV_724 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Incertae_Sedis |
| 102 | 1.51e-03 | ASV_783 | Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group |
| 103 | 1.51e-03 | ASV_795 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001 |
| 104 | 1.51e-03 | ASV_8 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum |
| 106 | 1.51e-03 | ASV_815 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004 |
| 107 | 1.51e-03 | ASV_819 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor |
| 108 | 1.51e-03 | ASV_837 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter |
| 109 | 1.51e-03 | ASV_886 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group |
| 111 | 1.51e-03 | ASV_90 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella |
| 112 | 1.51e-03 | ASV_902 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002 |
| 113 | 1.51e-03 | ASV_953 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group |
| 114 | 1.51e-03 | ASV_963 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter |
| 9 | 2.77e-03 | ASV_1100 | Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium |
| 14 | 2.77e-03 | ASV_117 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus |
| 19 | 2.77e-03 | ASV_1258 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006 |
| 27 | 2.77e-03 | ASV_1615 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006 |
| 80 | 2.77e-03 | ASV_450 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter |
| 87 | 2.77e-03 | ASV_534 | Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia |
| 95 | 2.77e-03 | ASV_66 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum |
| 110 | 2.77e-03 | ASV_893 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Oscillibacter |
| 59 | 4.06e-03 | ASV_29 | Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2 |
| 101 | 4.06e-03 | ASV_757 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1 |
| 22 | 4.96e-03 | ASV_1366 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio |
| 24 | 4.96e-03 | ASV_1434 | Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum |
| 40 | 4.96e-03 | ASV_2079 | Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter |
| 44 | 4.96e-03 | ASV_2217 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides |
| 49 | 4.96e-03 | ASV_2319 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter |
| 51 | 4.96e-03 | ASV_2357 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Sporobacter |
| 56 | 4.96e-03 | ASV_2540 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium |
| 74 | 4.96e-03 | ASV_3830 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium |
| 105 | 4.96e-03 | ASV_80 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group |
| 76 | 7.30e-03 | ASV_3930 | Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium |
| 89 | 7.30e-03 | ASV_563 | Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium |
| 48 | 1.31e-02 | ASV_2306 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001 |
| 75 | 1.31e-02 | ASV_3902 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_UBA1819 |
| 34 | 1.88e-02 | ASV_1915 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005 |
| 45 | 1.88e-02 | ASV_2220 | Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_Pirellula |
| 62 | 1.97e-02 | ASV_303 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003 |
| 72 | 2.30e-02 | ASV_3758 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens |
| 39 | 2.62e-02 | ASV_2068 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1 |
These are taxa that are differentailly abundant between grab samples and feces and their false discovery corrected p-value. ASVs are listed by significance.
## OTU Table: [1 taxa and 24 samples]
## taxa are rows
## 293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369 370
## ASV_1 114 124 177 280 224 295 298 281 230 204 170 216 4 8 4 7 8
## 371 372 373 374 375 376 378
## ASV_1 8 6 5 9 4 0 1
##
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1,
## data = ps_sub_gen)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.47780 0.07625 -19.380 0.00000000000155 ***
## Sample_TypeFeces -0.95570 0.06216 -15.375 0.00000000005273 ***
## CowIDCow_2477 0.18844 0.08258 2.282 0.0365 *
## CowIDCow_2549 -0.05694 0.08660 -0.657 0.5202
## CowIDCow_796 0.15162 0.08276 1.832 0.0856 .
## DayDay_7 -0.07839 0.07259 -1.080 0.2962
## DayDay_9 0.04504 0.07120 0.633 0.5359
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.089 0.312 -19.52 0.0000000000014 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -143.94
This is the feature table for ASV_1, let’s graph out this most significantly differentially abundant ASV Christensenellaceae_R-7_group. There is significantly less of this taxa in feces compared to grab samples. The day did not effect this, but there was significant cow differences in abundance.
Here we see that Christensenellaceae_R-7_group is more abundant in feces vs grab samples. In fact if we look at the feature table above we see this taxa is almost not present in the rumen grab samples.
We will remove other a few sample types to compress the data down and look just at the grab sample and stomach tube.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 4690 taxa and 56 samples ]
## sample_data() Sample Data: [ 56 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 4690 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 4690 tips and 4688 internal nodes ]
After subsetting the data we have 4,690 ASVs in 56 samples.
## [1] 4690
## [1] 20
## [1] 74
## [1] 110
## [1] 279
Previously, there are 5485 ASVs in the dataset. This was composed of 21 phyla, 78 Orders, 116 Families and 293 Genera. In the new subset we have 4690 ASVs in the dataset. This is composed of 20 phyla, 74 Orders, 110 Families and 279 Genera.
Again we will transformed the data for some exploratory analysis.
## Scale for 'colour' is already present. Adding another scale for
## 'colour', which will replace the existing scale.
Here we begin to see that Stomach Tube samples are more variable than the grab sample. Liquid strained samples seem to be the most variable (maybe comprable to stomach tube samples). Additionally, there seems to be two clusters for stomach tube samples (it’s probably not significant though). Potentially due to the presence of fiber in the sample or not?
From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining almost 90% of the variance between the samples.
Now that we take into account phylogenetic information in the distance metric there is a lot more variation explained. The first Axsis contains more variation that the second and mostly separates liquid (strained and unstrained) and some stomach tube samples from solid and grab samples.
Let’s make a figure with Weighted unifrac with and without the fecal samples
The eigenvalues here show the variation is spread across many axis, thus a 3D graph is best. You can find it hosted online here.
## No trace type specified:
## Based on info supplied, a 'scatter3d' trace seems appropriate.
## Read more about this trace type -> https://plot.ly/r/reference/#scatter3d
## No scatter3d mode specifed:
## Setting the mode to markers
## Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode
As before less of the variation is explained in each axis with the unweighted versus the weighted unifrac. Thus it seems that the difference between sample types is due to abundance differences and less about differences in species. We also, see the two clusters of stomach tube samples appearing again. This strengthens the hypothesis that stomach tube samples are more variable than grab samples and that there a minor taxa that explain differences between stomach tube samples. Addtionally, it looks like the two clusters of stomach tube samples might be forming due to individual cow differences (not a breed difference). Liquid sample remain different from grab and stomach tube samples.
The eigenvalues here show 2 axis are sufficient to capture most of the total variation.
We see again that the 1st axis corresponds is separtating liquid strained and unstrained samples from other rumen samples. This plot suggest there are more Bacteroidetes and Kiritimatiellaeota in the liquid samples, while rumen samples have more Firmicutes. This can also be seen in the first DPCoA we made where we said that Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Thus, we will probably only need to have one DPCoA graph in the paper.
We should see what taxa are differentially more or less abundant in grab sample vs other rumen sample types.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 278 taxa and 56 samples ]
## sample_data() Sample Data: [ 56 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 278 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 278 tips and 277 internal nodes ]
There are 278 genera in the rumen sample types.
99 taxa could not be fit with the model, but 179 were fit to the model and 108 were significantly differentially abundant genera p<0.05. 87 were significantly differentially abundant genera p<0.01. Lastly, 87 were significantly differentially abundant taxa p<0.05.
First, we will check if into the genera could not be fit to the model and see if we can determine why.
## OTU Table: [99 taxa and 56 samples]
## taxa are rows
## 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_5569 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_204 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_4099 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_878 4 9 0 0 2 0 0 0 1 2 1 6 5 4 0 0
## ASV_5218 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 0
## ASV_724 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_5230 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5009 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_2417 2 1 2 2 1 0 0 0 0 0 1 0 0 1 0 0
## ASV_2322 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_113 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_147 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5397 0 0 0 0 0 0 0 3 2 0 2 0 0 0 0 0
## ASV_4951 0 1 1 1 0 0 2 4 0 0 0 0 0 0 0 0
## ASV_5246 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0
## ASV_4383 0 0 1 0 2 0 1 1 2 2 0 0 0 0 1 2
## ASV_5288 0 2 0 0 1 0 0 0 0 0 1 0 0 0 1 2
## ASV_5123 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1258 1 4 1 0 3 3 1 0 11 1 1 1 1 1 2 2
## ASV_5496 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_4673 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3469 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0 0
## ASV_4670 0 2 1 0 2 0 0 0 0 0 0 0 0 0 0 0
## ASV_5204 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4857 0 1 5 0 0 1 2 0 2 0 0 0 0 0 0 0
## ASV_5547 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4998 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4508 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_2399 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5206 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1728 0 0 3 0 0 1 0 0 0 0 0 0 0 1 0 0
## ASV_1078 0 5 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_4258 1 1 8 2 2 1 0 0 1 0 1 0 0 0 0 0
## ASV_2658 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
## ASV_2389 2 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_1853 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4912 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5382 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2915 0 0 16 4 5 3 1 1 0 0 0 0 0 0 1 0
## ASV_4015 1 0 0 1 5 1 1 1 2 2 0 1 0 1 0 0
## ASV_4126 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 2
## ASV_4688 0 0 1 0 1 3 2 1 0 0 0 0 0 0 0 0
## ASV_4324 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4605 0 0 0 0 0 2 0 1 0 0 12 0 0 0 0 0
## ASV_5222 0 0 2 1 2 0 0 1 1 0 0 0 0 0 0 1
## ASV_5594 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3987 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5262 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_2401 0 0 1 4 0 0 0 0 0 0 0 0 1 0 0 1
## ASV_4992 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_1856 0 0 1 0 2 0 0 0 0 0 2 0 0 0 0 0
## ASV_3262 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 0
## ASV_5025 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4151 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5107 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4913 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3684 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4353 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4378 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0
## ASV_1247 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3201 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_2076 0 0 0 0 3 1 0 0 0 0 0 0 0 0 0 0
## ASV_3120 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_2445 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1307 0 2 0 0 0 1 0 0 1 0 0 0 0 0 0 0
## ASV_5210 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2550 2 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0
## ASV_4422 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3119 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5444 0 2 0 0 0 0 0 1 0 0 0 0 1 0 0 1
## ASV_2687 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4612 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0
## ASV_5614 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1213 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0
## ASV_5192 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5595 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4629 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5584 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5568 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3905 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5108 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5036 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_5532 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5269 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4849 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_3829 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1688 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1448 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_1756 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4267 0 3 1 1 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_4142 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0
## ASV_4771 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_5492 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3902 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_4822 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_893 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_1679 1 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0
## ASV_4340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_5569 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0
## ASV_204 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4099 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_878 3 0 0 0 4 6 2 4 2 2 2 0 3 0 2 4
## ASV_5218 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 0
## ASV_724 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5230 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0
## ASV_5009 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2417 0 0 0 0 1 0 1 2 2 3 2 2 2 0 1 1
## ASV_2322 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_113 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_147 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5397 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_5246 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0
## ASV_4383 1 0 0 0 0 1 0 0 0 0 1 1 1 0 0 0
## ASV_5288 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_5123 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_1258 4 2 0 1 2 1 5 0 1 2 2 0 0 0 2 4
## ASV_5496 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4673 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3469 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_4670 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5204 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4857 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0
## ASV_5547 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4998 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0
## ASV_4508 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2399 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_5206 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1728 0 0 0 0 0 0 0 0 2 0 1 0 0 1 0 2
## ASV_1078 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_4258 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_2658 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1
## ASV_2389 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_1853 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_4912 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0
## ASV_5382 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2915 0 0 0 0 0 0 0 1 0 0 0 1 1 0 1 0
## ASV_4015 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1
## ASV_4126 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_4688 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_4324 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
## ASV_4605 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5222 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_5594 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_3987 1 0 0 0 0 0 0 0 0 0 0 1 6 0 0 0
## ASV_5262 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_2401 0 0 0 0 0 0 0 0 0 0 0 5 0 2 0 0
## ASV_4992 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1856 1 0 0 1 0 0 0 2 0 0 0 0 0 0 0 0
## ASV_3262 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1
## ASV_5025 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4151 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## ASV_5107 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_4913 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0
## ASV_3684 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4353 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4378 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0
## ASV_1247 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3201 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2076 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 1
## ASV_3120 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2445 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0
## ASV_1307 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0
## ASV_5210 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2550 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4422 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_3119 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## ASV_5444 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_2687 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_4612 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0
## ASV_5614 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1213 0 0 0 0 0 1 0 0 0 0 2 0 1 0 0 3
## ASV_5192 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5595 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_4629 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5584 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5568 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3905 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0
## ASV_5108 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5036 0 1 0 0 2 0 0 0 0 1 0 0 0 0 0 0
## ASV_5532 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5269 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4849 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0
## ASV_3829 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1688 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_1448 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1756 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4267 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0
## ASV_4142 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0
## ASV_4771 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## ASV_5492 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3902 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4822 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_893 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_1679 0 0 0 0 0 0 0 11 5 9 3 3 9 0 0 3
## ASV_4340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 360 361 362 363 365 379 380 381 382 383 384 385 386 387 388 389
## ASV_5569 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_204 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4099 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 3
## ASV_878 1 4 0 0 0 6 10 2 0 2 5 0 0 0 2 8
## ASV_5218 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 2
## ASV_724 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_5230 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5009 0 0 1 0 0 0 0 0 0 0 3 0 0 0 0 0
## ASV_2417 1 0 0 0 2 0 0 0 1 0 0 0 0 0 0 0
## ASV_2322 1 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0
## ASV_113 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0
## ASV_147 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5397 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4951 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5246 0 1 0 0 0 0 0 0 2 1 0 0 0 0 0 0
## ASV_4383 1 1 0 0 0 0 0 0 2 0 1 1 0 0 0 1
## ASV_5288 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0
## ASV_5123 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_5340 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_1258 1 4 4 2 1 1 2 7 6 1 2 3 2 1 5 1
## ASV_5496 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1
## ASV_4673 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3469 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_4670 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0
## ASV_5204 0 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0
## ASV_4857 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5547 0 3 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_4998 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4508 1 0 1 0 0 0 0 0 0 0 4 0 0 0 1 1
## ASV_2399 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5206 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1728 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1078 0 4 0 0 0 0 1 0 0 0 0 0 1 0 0 0
## ASV_4258 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2658 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1
## ASV_2389 2 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0
## ASV_1853 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1
## ASV_4912 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5382 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2915 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_4015 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4126 4 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## ASV_4688 0 0 2 0 0 0 0 0 0 0 0 0 1 2 0 0
## ASV_4324 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_4605 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5222 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5594 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_3987 0 6 0 0 0 0 0 0 0 0 11 0 0 0 0 0
## ASV_5262 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2401 7 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4992 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_1856 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
## ASV_3262 0 0 0 0 0 1 0 0 3 1 1 0 0 0 0 0
## ASV_5025 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
## ASV_4151 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5107 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## ASV_4913 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_3684 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4353 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4378 1 0 0 0 1 0 0 0 2 0 0 0 3 0 0 1
## ASV_1247 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3201 0 0 0 0 0 0 0 0 1 0 2 0 0 0 0 0
## ASV_2076 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_3120 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## ASV_2445 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_1307 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0
## ASV_5210 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2550 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0
## ASV_4422 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3119 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5444 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_2687 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0
## ASV_4612 0 0 0 0 0 1 0 1 2 2 0 1 2 0 1 0
## ASV_5614 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1213 1 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0
## ASV_5192 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
## ASV_5595 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4629 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5584 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_5568 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
## ASV_3905 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_5108 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0
## ASV_5036 0 0 0 0 0 2 0 0 0 0 1 1 1 0 0 0
## ASV_5532 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_5269 0 3 0 0 0 0 0 0 1 0 4 0 0 0 0 0
## ASV_4849 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
## ASV_3829 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
## ASV_1688 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1448 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_1756 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_4267 0 1 0 0 1 3 1 0 1 0 0 0 3 1 1 0
## ASV_4142 0 0 0 0 0 0 1 0 2 0 0 0 1 0 0 1
## ASV_4771 0 0 1 0 0 0 0 0 0 0 0 0 3 0 1 0
## ASV_5492 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_3902 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
## ASV_4822 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## ASV_893 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
## ASV_1679 8 2 2 2 4 0 0 0 0 0 0 0 0 0 0 0
## ASV_4340 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1 0
## 390 505 506 507 508 509 510 511
## ASV_5569 0 0 0 0 0 0 0 0
## ASV_204 0 0 0 0 0 1 0 0
## ASV_4099 0 0 0 1 0 0 0 0
## ASV_878 0 0 0 3 0 6 6 7
## ASV_5218 0 0 0 0 0 0 1 0
## ASV_724 0 0 0 0 0 1 1 0
## ASV_5230 0 0 1 0 0 1 0 0
## ASV_5009 0 0 0 0 0 0 0 0
## ASV_2417 0 0 0 2 0 8 1 3
## ASV_2322 0 0 0 0 0 2 0 0
## ASV_113 0 0 1 0 0 0 0 0
## ASV_147 0 0 0 0 0 0 1 0
## ASV_5397 0 0 0 0 0 0 0 0
## ASV_4951 0 0 0 0 0 0 0 0
## ASV_5246 0 0 0 0 1 0 0 0
## ASV_4383 0 0 0 0 0 2 0 1
## ASV_5288 0 0 0 0 0 0 0 0
## ASV_5123 0 0 0 0 0 1 0 0
## ASV_5340 0 0 0 0 0 3 1 0
## ASV_1258 2 0 2 0 0 4 0 1
## ASV_5496 0 0 0 0 0 0 0 0
## ASV_4673 0 0 0 0 0 0 0 0
## ASV_3469 0 0 0 0 0 2 1 0
## ASV_4670 0 0 0 0 1 0 0 0
## ASV_5204 0 0 0 0 0 1 1 0
## ASV_4857 0 0 0 0 0 0 0 0
## ASV_5547 0 0 0 0 0 0 0 0
## ASV_4998 0 0 0 0 0 1 0 0
## ASV_4508 0 0 0 0 1 2 0 0
## ASV_2399 0 0 0 0 0 0 1 0
## ASV_5206 0 0 0 0 0 1 0 0
## ASV_1728 0 0 0 0 0 1 0 0
## ASV_1078 0 0 0 0 0 0 0 0
## ASV_4258 0 0 0 0 0 0 0 0
## ASV_2658 0 0 0 0 0 0 1 0
## ASV_2389 0 0 0 0 0 1 0 0
## ASV_1853 0 1 0 0 0 0 1 0
## ASV_4912 0 0 0 0 0 0 0 0
## ASV_5382 0 0 0 0 0 2 0 0
## ASV_2915 0 0 0 0 0 0 0 0
## ASV_4015 0 0 1 0 0 0 0 0
## ASV_4126 0 0 0 0 1 0 0 1
## ASV_4688 0 0 1 0 0 0 0 0
## ASV_4324 0 0 0 0 0 1 0 0
## ASV_4605 0 0 0 0 1 0 0 0
## ASV_5222 0 0 0 0 0 0 0 0
## ASV_5594 0 0 0 0 0 0 0 0
## ASV_3987 0 0 0 0 0 0 0 0
## ASV_5262 0 0 0 0 0 0 0 0
## ASV_2401 0 1 0 0 0 1 0 0
## ASV_4992 0 0 1 0 0 0 0 0
## ASV_1856 2 0 0 0 1 1 0 0
## ASV_3262 0 0 1 0 0 0 0 0
## ASV_5025 0 0 0 0 0 0 0 0
## ASV_4151 0 0 0 0 0 0 0 0
## ASV_5107 0 0 0 0 1 0 0 1
## ASV_4913 0 0 0 0 0 1 0 2
## ASV_3684 0 0 0 0 0 0 1 0
## ASV_4353 0 0 0 0 0 0 0 1
## ASV_4378 0 0 0 0 0 2 0 1
## ASV_1247 0 0 0 0 0 0 2 0
## ASV_3201 0 0 0 0 0 0 0 0
## ASV_2076 0 0 0 0 0 0 0 0
## ASV_3120 0 0 0 0 0 0 0 2
## ASV_2445 0 0 0 0 0 0 0 0
## ASV_1307 0 0 0 0 0 0 0 0
## ASV_5210 0 0 0 0 0 0 0 0
## ASV_2550 0 0 2 0 0 1 1 0
## ASV_4422 0 0 0 0 0 1 0 2
## ASV_3119 0 0 1 0 0 1 0 0
## ASV_5444 0 0 0 1 0 0 0 0
## ASV_2687 0 0 0 0 0 0 2 2
## ASV_4612 0 1 0 0 0 0 0 0
## ASV_5614 0 0 0 0 0 2 0 0
## ASV_1213 0 0 1 0 0 1 0 0
## ASV_5192 0 0 0 0 0 0 0 0
## ASV_5595 0 0 0 0 0 0 0 0
## ASV_4629 0 0 0 0 0 0 0 0
## ASV_5584 0 0 0 0 0 0 0 1
## ASV_5568 0 0 0 0 0 0 1 0
## ASV_3905 0 0 0 0 0 0 2 0
## ASV_5108 0 0 0 0 0 0 0 0
## ASV_5036 0 0 0 0 0 0 0 0
## ASV_5532 0 0 0 0 0 0 0 0
## ASV_5269 0 0 0 0 0 0 0 0
## ASV_4849 0 0 0 0 0 1 0 0
## ASV_3829 0 0 0 0 0 0 0 0
## ASV_1688 0 0 0 0 0 0 0 0
## ASV_1448 0 0 0 0 0 0 0 0
## ASV_1756 0 0 0 0 0 0 1 0
## ASV_4267 0 0 0 0 0 0 0 0
## ASV_4142 1 0 0 1 1 1 1 2
## ASV_4771 0 0 0 0 0 3 1 0
## ASV_5492 0 0 1 0 0 0 0 0
## ASV_3902 0 0 0 0 0 1 0 0
## ASV_4822 0 1 0 0 0 0 0 0
## ASV_893 0 0 0 1 0 3 1 0
## ASV_1679 0 1 4 2 1 11 4 17
## ASV_4340 0 0 0 0 0 0 0 0
Yikes, 99 taxa could not be fit with the model, but this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type.
Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:
## [1] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FE2018_group"
## [2] "Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group"
## [3] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group"
## [4] "Firmicutes_Lachnospiraceae_Acetatifactor"
## [5] "Firmicutes_Lachnospiraceae_Howardella"
## [6] "Firmicutes_Lachnospiraceae_Marvinbryantia"
## [7] "Firmicutes_Lachnospiraceae_Blautia"
## [8] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK3A20_group"
## [9] "Firmicutes_Lachnospiraceae_XBB1006"
## [10] "Firmicutes_Lachnospiraceae_Roseburia"
## [11] "Firmicutes_Lachnospiraceae_Shuttleworthia"
## [12] "Firmicutes_Lachnospiraceae_Pseudobutyrivibrio"
## [13] "Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group"
## [14] "Firmicutes_Lachnospiraceae_Moryella"
## [15] "Firmicutes_Lachnospiraceae_Butyrivibrio_2"
## [16] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-002"
## [17] "Firmicutes_Lachnospiraceae_Acetitomaculum"
## [18] "Firmicutes_Lachnospiraceae_Lachnoclostridium_10"
## [19] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006"
## [20] "Firmicutes_Lachnospiraceae_Coprococcus_2"
## [21] "Firmicutes_Defluviitaleaceae_Defluviitaleaceae_UCG-011"
## [22] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-010"
## [23] "Firmicutes_Lachnospiraceae_Coprococcus_1"
## [24] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-008"
## [25] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group"
## [26] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-009"
## [27] "Firmicutes_Lachnospiraceae_Tyzzerella_3"
## [28] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014"
## [29] "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001"
## [30] "Firmicutes_Veillonellaceae_Quinella"
## [31] "Firmicutes_Veillonellaceae_Selenomonas_1"
## [32] "Firmicutes_Veillonellaceae_Schwartzia"
## [33] "Firmicutes_Veillonellaceae_Selenomonas_4"
## [34] "Firmicutes_Veillonellaceae_Anaerovibrio"
## [35] "Firmicutes_Family_XIII_Mogibacterium"
## [36] "Firmicutes_Family_XIII_Family_XIII_AD3011_group"
## [37] "Firmicutes_Family_XIII_Family_XIII_UCG-001"
## [38] "Firmicutes_Family_XIII_Anaerovorax"
## [39] "Tenericutes_Anaeroplasmataceae_Anaeroplasma"
## [40] "Firmicutes_Erysipelotrichaceae_Catenisphaera"
## [41] "Firmicutes_Erysipelotrichaceae_Solobacterium"
## [42] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009"
## [43] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004"
## [44] "Firmicutes_Streptococcaceae_Streptococcus"
## [45] "Firmicutes_Lactobacillaceae_Lactobacillus"
## [46] "Firmicutes_Staphylococcaceae_Staphylococcus"
## [47] "Firmicutes_Planococcaceae_Planococcus"
## [48] "Firmicutes_Clostridiaceae_1_Clostridium_sensu_stricto_1"
## [49] "Firmicutes_Acidaminococcaceae_Succiniclasticum"
## [50] "Firmicutes_Syntrophomonadaceae_Pelospora"
## [51] "Firmicutes_Eubacteriaceae_Anaerofustis"
## [52] "Elusimicrobia_Elusimicrobiaceae_Elusimicrobium"
## [53] "Proteobacteria_Pseudomonadaceae_Pseudomonas"
## [54] "Proteobacteria_Succinivibrionaceae_Succinimonas"
## [55] "Proteobacteria_Succinivibrionaceae_Anaerobiospirillum"
## [56] "Proteobacteria_Succinivibrionaceae_Succinivibrio"
## [57] "Proteobacteria_Burkholderiaceae_Sutterella"
## [58] "Proteobacteria_Burkholderiaceae_Variovorax"
## [59] "Proteobacteria_Burkholderiaceae_Massilia"
## [60] "Proteobacteria_Cardiobacteriaceae_Suttonella"
## [61] "Proteobacteria_Succinivibrionaceae_Ruminobacter"
## [62] "Proteobacteria_Succinivibrionaceae_Succinivibrionaceae_UCG-002"
## [63] "Proteobacteria_Desulfobulbaceae_Desulfobulbus"
## [64] "Fusobacteria_Fusobacteriaceae_Fusobacterium"
## [65] "Euryarchaeota_Methanobacteriaceae_Methanosphaera"
## [66] "Euryarchaeota_Methanomethylophilaceae_Candidatus_Methanomethylophilus"
## [67] "Proteobacteria_Desulfovibrionaceae_Desulfovibrio"
## [68] "Proteobacteria_Desulfovibrionaceae_Mailhella"
## [69] "Proteobacteria_Desulfuromonadaceae_Desulfuromonas"
## [70] "Spirochaetes_Spirochaetaceae_M2PT2-76_termite_group"
## [71] "Actinobacteria_Corynebacteriaceae_Corynebacterium"
## [72] "Actinobacteria_Nocardiaceae_Rhodococcus"
## [73] "Actinobacteria_Coriobacteriales_Incertae_Sedis_Raoultibacter"
## [74] "Actinobacteria_Eggerthellaceae_DNF00809"
## [75] "Actinobacteria_Atopobiaceae_Olsenella"
## [76] "Actinobacteria_Atopobiaceae_Atopobium"
## [77] "Fibrobacteres_Fibrobacteraceae_Fibrobacter"
## [78] "Chloroflexi_Anaerolineaceae_Flexilinea"
## [79] "Synergistetes_Synergistaceae_Pyramidobacter"
## [80] "Firmicutes_Christensenellaceae_Christensenellaceae_R-7_group"
## [81] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-010"
## [82] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003"
## [83] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-004"
## [84] "Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group"
## [85] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-001"
## [86] "Bacteroidetes_Prevotellaceae_Prevotella_1"
## [87] "Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group"
## [88] "Bacteroidetes_Prevotellaceae_Prevotellaceae_YAB2003_group"
## [89] "Bacteroidetes_Rikenellaceae_Rikenellaceae_RC9_gut_group"
## [90] "Bacteroidetes_Rikenellaceae_U29-B03"
## [91] "Bacteroidetes_Porphyromonadaceae_Porphyromonas"
## [92] "Firmicutes_Ruminococcaceae_Ruminiclostridium_6"
## [93] "Firmicutes_Ruminococcaceae_Ruminococcus_1"
## [94] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001"
## [95] "Firmicutes_Ruminococcaceae_Ruminococcus_2"
## [96] "Firmicutes_Ruminococcaceae_CAG-352"
## [97] "Firmicutes_Ruminococcaceae_Saccharofermentans"
## [98] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013"
## [99] "Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group"
## [100] "Firmicutes_Ruminococcaceae_Papillibacter"
## [101] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-005"
## [102] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-002"
## [103] "Firmicutes_Ruminococcaceae_Ruminiclostridium_9"
## [104] "Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group"
## [105] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004"
## [106] "Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group"
## [107] "Firmicutes_Lachnospiraceae_possible_genus_Sk018"
## [108] "Firmicutes_Lachnospiraceae_probable_genus_10"
There are 108 genera differentially abundant. We will look at the unique families they represent.
| Var1 | Freq |
|---|---|
| Firmicutes_Lachnospiraceae | 29 |
| Firmicutes_Ruminococcaceae | 16 |
| Bacteroidetes_Prevotellaceae | 7 |
| Firmicutes_Veillonellaceae | 6 |
| Proteobacteria_Succinivibrionaceae | 5 |
| Firmicutes_Erysipelotrichaceae | 4 |
| Firmicutes_Family_XIII | 4 |
| Proteobacteria_Burkholderiaceae | 3 |
| Actinobacteria_Atopobiaceae | 2 |
| Bacteroidetes_Rikenellaceae | 2 |
| Proteobacteria_Desulfovibrionaceae | 2 |
| Actinobacteria_Coriobacteriales_Incertae_Sedis | 1 |
| Actinobacteria_Corynebacteriaceae | 1 |
| Actinobacteria_Eggerthellaceae | 1 |
| Actinobacteria_Nocardiaceae | 1 |
| Bacteroidetes_Porphyromonadaceae | 1 |
| Chloroflexi_Anaerolineaceae | 1 |
| Elusimicrobia_Elusimicrobiaceae | 1 |
| Euryarchaeota_Methanobacteriaceae | 1 |
| Euryarchaeota_Methanomethylophilaceae | 1 |
| Fibrobacteres_Fibrobacteraceae | 1 |
| Firmicutes_Acidaminococcaceae | 1 |
| Firmicutes_Christensenellaceae | 1 |
| Firmicutes_Clostridiaceae_1 | 1 |
| Firmicutes_Defluviitaleaceae | 1 |
| Firmicutes_Eubacteriaceae | 1 |
| Firmicutes_Lactobacillaceae | 1 |
| Firmicutes_Planococcaceae | 1 |
| Firmicutes_Staphylococcaceae | 1 |
| Firmicutes_Streptococcaceae | 1 |
| Firmicutes_Syntrophomonadaceae | 1 |
| Fusobacteria_Fusobacteriaceae | 1 |
| Proteobacteria_Cardiobacteriaceae | 1 |
| Proteobacteria_Desulfobulbaceae | 1 |
| Proteobacteria_Desulfuromonadaceae | 1 |
| Proteobacteria_Pseudomonadaceae | 1 |
| Spirochaetes_Spirochaetaceae | 1 |
| Synergistetes_Synergistaceae | 1 |
| Tenericutes_Anaeroplasmataceae | 1 |
From this we can see that Lachnospiraceae, Ruminococcaceae, and Prevotellaceae were the most common families to be differentially abundant in grab samples vs other rumen sample types. We will take a closer look at all ASVs differentially abundant.
| p_value | ASV | Taxa | |
|---|---|---|---|
| 1 | 2.43e-03 | ASV_1 | Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group |
| 2 | 2.43e-03 | ASV_10 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans |
| 3 | 2.43e-03 | ASV_1016 | Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis |
| 4 | 2.43e-03 | ASV_103 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1 |
| 5 | 2.43e-03 | ASV_105 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group |
| 6 | 2.43e-03 | ASV_1130 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018 |
| 7 | 2.43e-03 | ASV_1132 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group |
| 8 | 2.43e-03 | ASV_1161 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006 |
| 9 | 2.43e-03 | ASV_117 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus |
| 10 | 2.43e-03 | ASV_120 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002 |
| 11 | 2.43e-03 | ASV_124 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group |
| 12 | 2.43e-03 | ASV_1366 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio |
| 13 | 2.43e-03 | ASV_1372 | Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium |
| 15 | 2.43e-03 | ASV_14 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium |
| 16 | 2.43e-03 | ASV_1403 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella |
| 17 | 2.43e-03 | ASV_141 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrio |
| 18 | 2.43e-03 | ASV_145 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group |
| 21 | 2.43e-03 | ASV_154 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004 |
| 25 | 2.43e-03 | ASV_172 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809 |
| 26 | 2.43e-03 | ASV_176 | Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas |
| 27 | 2.43e-03 | ASV_183 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014 |
| 29 | 2.43e-03 | ASV_192 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group |
| 30 | 2.43e-03 | ASV_2 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group |
| 31 | 2.43e-03 | ASV_20 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1 |
| 32 | 2.43e-03 | ASV_201 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group |
| 33 | 2.43e-03 | ASV_210 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10 |
| 39 | 2.43e-03 | ASV_2183 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3 |
| 40 | 2.43e-03 | ASV_22 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella |
| 41 | 2.43e-03 | ASV_2244 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Schwartzia |
| 42 | 2.43e-03 | ASV_23 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1 |
| 44 | 2.43e-03 | ASV_235 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1 |
| 45 | 2.43e-03 | ASV_2419 | Bacteria_Proteobacteria_Gammaproteobacteria_Cardiobacteriales_Cardiobacteriaceae_Suttonella |
| 46 | 2.43e-03 | ASV_246 | Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma |
| 47 | 2.43e-03 | ASV_248 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group |
| 48 | 2.43e-03 | ASV_25 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio |
| 49 | 2.43e-03 | ASV_2517 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Quinella |
| 51 | 2.43e-03 | ASV_298 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax |
| 53 | 2.43e-03 | ASV_305 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013 |
| 54 | 2.43e-03 | ASV_311 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella |
| 57 | 2.43e-03 | ASV_320 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10 |
| 60 | 2.43e-03 | ASV_348 | Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011 |
| 61 | 2.43e-03 | ASV_357 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002 |
| 62 | 2.43e-03 | ASV_37 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter |
| 63 | 2.43e-03 | ASV_376 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group |
| 65 | 2.43e-03 | ASV_399 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2 |
| 66 | 2.43e-03 | ASV_4 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group |
| 68 | 2.43e-03 | ASV_418 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium |
| 71 | 2.43e-03 | ASV_428 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia |
| 72 | 2.43e-03 | ASV_429 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetatifactor |
| 73 | 2.43e-03 | ASV_439 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella |
| 75 | 2.43e-03 | ASV_450 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter |
| 77 | 2.43e-03 | ASV_457 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008 |
| 78 | 2.43e-03 | ASV_462 | Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium |
| 80 | 2.43e-03 | ASV_471 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium |
| 81 | 2.43e-03 | ASV_474 | Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001 |
| 82 | 2.43e-03 | ASV_499 | Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Pyramidobacter |
| 83 | 2.43e-03 | ASV_511 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinimonas |
| 84 | 2.43e-03 | ASV_520 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus |
| 86 | 2.43e-03 | ASV_57 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia |
| 88 | 2.43e-03 | ASV_636 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009 |
| 89 | 2.43e-03 | ASV_656 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter |
| 90 | 2.43e-03 | ASV_66 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum |
| 92 | 2.43e-03 | ASV_670 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia |
| 94 | 2.43e-03 | ASV_68 | Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter |
| 95 | 2.43e-03 | ASV_71 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2 |
| 96 | 2.43e-03 | ASV_72 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001 |
| 97 | 2.43e-03 | ASV_733 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004 |
| 98 | 2.43e-03 | ASV_793 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-006 |
| 99 | 2.43e-03 | ASV_8 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum |
| 100 | 2.43e-03 | ASV_83 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9 |
| 102 | 2.43e-03 | ASV_90 | Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella |
| 104 | 2.43e-03 | ASV_902 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002 |
| 105 | 2.43e-03 | ASV_91 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003 |
| 108 | 2.43e-03 | ASV_970 | Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Anaerobiospirillum |
| 22 | 4.59e-03 | ASV_16 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group |
| 23 | 4.59e-03 | ASV_1658 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_U29-B03 |
| 28 | 4.59e-03 | ASV_184 | Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera |
| 70 | 4.59e-03 | ASV_4270 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Porphyromonadaceae_Porphyromonas |
| 38 | 6.56e-03 | ASV_2174 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Variovorax |
| 56 | 6.56e-03 | ASV_3188 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_CAG-352 |
| 93 | 6.56e-03 | ASV_674 | Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera |
| 101 | 6.56e-03 | ASV_887 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group |
| 34 | 8.25e-03 | ASV_212 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010 |
| 74 | 8.25e-03 | ASV_44 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005 |
| 103 | 8.25e-03 | ASV_901 | Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_M2PT2-76_termite_group |
| 106 | 8.25e-03 | ASV_921 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010 |
| 107 | 8.25e-03 | ASV_953 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group |
| 43 | 1.01e-02 | ASV_2300 | Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1 |
| 67 | 1.01e-02 | ASV_409 | Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea |
| 19 | 1.16e-02 | ASV_149 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio |
| 50 | 1.16e-02 | ASV_2617 | Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_YAB2003_group |
| 55 | 1.16e-02 | ASV_3129 | Bacteria_Firmicutes_Clostridia_Clostridiales_Syntrophomonadaceae_Pelospora |
| 64 | 1.16e-02 | ASV_3936 | Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus |
| 14 | 1.70e-02 | ASV_1389 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfuromonadales_Desulfuromonadaceae_Desulfuromonas |
| 24 | 1.70e-02 | ASV_169 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004 |
| 58 | 2.38e-02 | ASV_3273 | Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium |
| 76 | 2.38e-02 | ASV_456 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Veillonellaceae_UCG-001 |
| 91 | 2.38e-02 | ASV_669 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Shuttleworthia |
| 37 | 2.53e-02 | ASV_2171 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-001 |
| 36 | 2.88e-02 | ASV_2134 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2 |
| 79 | 3.19e-02 | ASV_4697 | Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_4 |
| 52 | 4.40e-02 | ASV_2981 | Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus |
| 20 | 4.52e-02 | ASV_1509 | Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus |
| 35 | 4.52e-02 | ASV_2130 | Bacteria_Proteobacteria_Deltaproteobacteria_Desulfobacterales_Desulfobulbaceae_Desulfobulbus |
| 59 | 4.52e-02 | ASV_3393 | Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus |
| 69 | 4.52e-02 | ASV_423 | Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Massilia |
| 87 | 4.52e-02 | ASV_601 | Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009 |
| 85 | 4.64e-02 | ASV_560 | Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6 |
Taking a closer look at the break down of Fibrobacteraceae
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
## Family Genus Species
## ASV_68 "Fibrobacteraceae" NA NA
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -3.80549 0.13890 -27.397
## Sample_TypeStomach Tube -1.75544 0.21039 -8.344
## Sample_TypeLiquid Strained -0.13258 0.12873 -1.030
## Sample_TypeSolid -0.44736 0.13872 -3.225
## Sample_TypeLiquid Unstrained -0.91152 0.18408 -4.952
## CowIDCow_2477 0.19984 0.13799 1.448
## CowIDCow_2549 0.04026 0.14421 0.279
## CowIDCow_796 -0.07145 0.14797 -0.483
## DayDay_7 -0.10136 0.13020 -0.778
## DayDay_9 0.11523 0.11857 0.972
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.00000000011 ***
## Sample_TypeLiquid Strained 0.30854
## Sample_TypeSolid 0.00235 **
## Sample_TypeLiquid Unstrained 0.00001080133 ***
## CowIDCow_2477 0.15447
## CowIDCow_2549 0.78139
## CowIDCow_796 0.63152
## DayDay_7 0.44037
## DayDay_9 0.33635
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.2354 0.2076 -30.03 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -272.44
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -3.64488 0.14105 -25.841
## Sample_TypeStomach Tube -1.77488 0.21439 -8.279
## Sample_TypeLiquid Strained -0.10065 0.13002 -0.774
## Sample_TypeSolid -0.44883 0.14104 -3.182
## Sample_TypeLiquid Unstrained -0.89898 0.18617 -4.829
## CowIDCow_2477 0.20392 0.13940 1.463
## CowIDCow_2549 0.03105 0.14606 0.213
## CowIDCow_796 -0.07921 0.14981 -0.529
## DayDay_7 -0.09707 0.13200 -0.735
## DayDay_9 0.12889 0.12009 1.073
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.000000000136 ***
## Sample_TypeLiquid Strained 0.44289
## Sample_TypeSolid 0.00265 **
## Sample_TypeLiquid Unstrained 0.000016227326 ***
## CowIDCow_2477 0.15045
## CowIDCow_2549 0.83262
## CowIDCow_796 0.59961
## DayDay_7 0.46593
## DayDay_9 0.28886
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.0413 0.2073 -29.14 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -272.61
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_103 "Bacteria" "Firmicutes" "Clostridia" "Clostridiales"
## Family Genus Species
## ASV_103 "Ruminococcaceae" "Ruminococcus_1" NA
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -3.200533 0.079867 -40.073
## Sample_TypeStomach Tube -0.767638 0.092303 -8.316
## Sample_TypeLiquid Strained -0.424786 0.082959 -5.120
## Sample_TypeSolid 0.004558 0.073561 0.062
## Sample_TypeLiquid Unstrained -0.493629 0.094815 -5.206
## CowIDCow_2477 -0.129281 0.079632 -1.623
## CowIDCow_2549 0.066452 0.076700 0.866
## CowIDCow_796 0.007782 0.077747 0.100
## DayDay_7 -0.282765 0.071308 -3.965
## DayDay_9 -0.111542 0.063832 -1.747
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.00000000012 ***
## Sample_TypeLiquid Strained 0.00000615317 ***
## Sample_TypeSolid 0.95087
## Sample_TypeLiquid Unstrained 0.00000461602 ***
## CowIDCow_2477 0.11147
## CowIDCow_2549 0.39088
## CowIDCow_796 0.92072
## DayDay_7 0.00026 ***
## DayDay_9 0.08738 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.0052 0.2308 -30.36 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -268.16
Pulling out the model for Fibrobacteraceae
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
## Family Genus Species
## ASV_68 "Fibrobacteraceae" "Fibrobacter" NA
## [1] "Model for Fibrobacter"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -3.64488 0.14105 -25.841
## Sample_TypeStomach Tube -1.77488 0.21439 -8.279
## Sample_TypeLiquid Strained -0.10065 0.13002 -0.774
## Sample_TypeSolid -0.44883 0.14104 -3.182
## Sample_TypeLiquid Unstrained -0.89898 0.18617 -4.829
## CowIDCow_2477 0.20392 0.13940 1.463
## CowIDCow_2549 0.03105 0.14606 0.213
## CowIDCow_796 -0.07921 0.14981 -0.529
## DayDay_7 -0.09707 0.13200 -0.735
## DayDay_9 0.12889 0.12009 1.073
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.000000000136 ***
## Sample_TypeLiquid Strained 0.44289
## Sample_TypeSolid 0.00265 **
## Sample_TypeLiquid Unstrained 0.000016227326 ***
## CowIDCow_2477 0.15045
## CowIDCow_2549 0.83262
## CowIDCow_796 0.59961
## DayDay_7 0.46593
## DayDay_9 0.28886
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.0413 0.2073 -29.14 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -272.61
Graphing out all the families that are significantly different between grab samples and other rumen sample types.
Pulling out the model for genera in Prevotellaceae here.
## Taxonomy Table: [7 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_91 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_154 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_201 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_72 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_20 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_1132 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_2617 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## Family Genus Species
## ASV_91 "Prevotellaceae" "Prevotellaceae_UCG-003" NA
## ASV_154 "Prevotellaceae" "Prevotellaceae_UCG-004" NA
## ASV_201 "Prevotellaceae" "Prevotellaceae_Ga6A1_group" NA
## ASV_72 "Prevotellaceae" "Prevotellaceae_UCG-001" NA
## ASV_20 "Prevotellaceae" "Prevotella_1" NA
## ASV_1132 "Prevotellaceae" "Prevotellaceae_NK3B31_group" NA
## ASV_2617 "Prevotellaceae" "Prevotellaceae_YAB2003_group" NA
## [1] "Model for Prevotella_1"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -2.75424 0.11121 -24.766
## Sample_TypeStomach Tube 0.22141 0.11474 1.930
## Sample_TypeLiquid Strained 1.25445 0.10022 12.517
## Sample_TypeSolid 0.06410 0.11773 0.544
## Sample_TypeLiquid Unstrained 0.70775 0.11798 5.999
## CowIDCow_2477 0.09219 0.09069 1.017
## CowIDCow_2549 0.08058 0.09057 0.890
## CowIDCow_796 -0.01757 0.09205 -0.191
## DayDay_7 0.04570 0.08404 0.544
## DayDay_9 0.11046 0.07559 1.461
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.060 .
## Sample_TypeLiquid Strained 0.000000000000000293 ***
## Sample_TypeSolid 0.589
## Sample_TypeLiquid Unstrained 0.000000313650803771 ***
## CowIDCow_2477 0.315
## CowIDCow_2549 0.378
## CowIDCow_796 0.849
## DayDay_7 0.589
## DayDay_9 0.151
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.2565 0.1958 -26.84 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -347.35
## [1] "Model for Prevotellaceae_UCG-003"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -4.269117 0.098473 -43.353
## Sample_TypeStomach Tube 0.367820 0.100674 3.654
## Sample_TypeLiquid Strained 1.162644 0.089297 13.020
## Sample_TypeSolid 0.007731 0.107603 0.072
## Sample_TypeLiquid Unstrained 0.885074 0.100617 8.796
## CowIDCow_2477 0.046630 0.077879 0.599
## CowIDCow_2549 0.162481 0.076833 2.115
## CowIDCow_796 0.053311 0.078707 0.677
## DayDay_7 -0.095193 0.072098 -1.320
## DayDay_9 0.031053 0.062622 0.496
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.000673 ***
## Sample_TypeLiquid Strained < 0.0000000000000002 ***
## Sample_TypeSolid 0.943044
## Sample_TypeLiquid Unstrained 0.0000000000246 ***
## CowIDCow_2477 0.552342
## CowIDCow_2549 0.040025 *
## CowIDCow_796 0.501657
## DayDay_7 0.193406
## DayDay_9 0.622390
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.0921 0.2334 -30.39 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -263.07
## [1] "Model for Prevotellaceae_UCG-004"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -5.47683 0.13755 -39.816
## Sample_TypeStomach Tube -0.09603 0.12682 -0.757
## Sample_TypeLiquid Strained -0.69899 0.15142 -4.616
## Sample_TypeSolid 0.30414 0.11276 2.697
## Sample_TypeLiquid Unstrained -0.23747 0.14817 -1.603
## CowIDCow_2477 0.10932 0.12497 0.875
## CowIDCow_2549 0.38583 0.11905 3.241
## CowIDCow_796 0.26012 0.12265 2.121
## DayDay_7 0.04305 0.10408 0.414
## DayDay_9 0.02275 0.09893 0.230
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.45285
## Sample_TypeLiquid Strained 0.0000326 ***
## Sample_TypeSolid 0.00980 **
## Sample_TypeLiquid Unstrained 0.11600
## CowIDCow_2477 0.38634
## CowIDCow_2549 0.00224 **
## CowIDCow_796 0.03948 *
## DayDay_7 0.68109
## DayDay_9 0.81918
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.1820 0.3045 -26.87 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -194.82
## [1] "Model for Prevotellaceae_UCG-001"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -4.48384 0.09140 -49.060
## Sample_TypeStomach Tube -0.04059 0.09828 -0.413
## Sample_TypeLiquid Strained 0.84341 0.08280 10.186
## Sample_TypeSolid 0.01873 0.09440 0.198
## Sample_TypeLiquid Unstrained 0.45009 0.09672 4.654
## CowIDCow_2477 -0.12107 0.07433 -1.629
## CowIDCow_2549 -0.12110 0.07549 -1.604
## CowIDCow_796 -0.16120 0.07646 -2.108
## DayDay_7 0.01508 0.07125 0.212
## DayDay_9 0.18122 0.06336 2.860
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.6816
## Sample_TypeLiquid Strained 0.000000000000291 ***
## Sample_TypeSolid 0.8436
## Sample_TypeLiquid Unstrained 0.000028859046887 ***
## CowIDCow_2477 0.1103
## CowIDCow_2549 0.1157
## CowIDCow_796 0.0406 *
## DayDay_7 0.8333
## DayDay_9 0.0064 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.7963 0.2788 -27.96 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -235.28
## [1] "Model for Prevotellaceae_NK3B31_group"
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -5.87144 0.16744 -35.066
## Sample_TypeStomach Tube -0.58858 0.19073 -3.086
## Sample_TypeLiquid Strained -1.08143 0.22449 -4.817
## Sample_TypeSolid 0.25058 0.14697 1.705
## Sample_TypeLiquid Unstrained -0.53659 0.21017 -2.553
## CowIDCow_2477 -0.50695 0.16957 -2.990
## CowIDCow_2549 -0.21946 0.15718 -1.396
## CowIDCow_796 -0.16570 0.15706 -1.055
## DayDay_7 -0.09407 0.14453 -0.651
## DayDay_9 -0.14163 0.13953 -1.015
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.00347 **
## Sample_TypeLiquid Strained 0.0000169 ***
## Sample_TypeSolid 0.09510 .
## Sample_TypeLiquid Unstrained 0.01414 *
## CowIDCow_2477 0.00452 **
## CowIDCow_2549 0.16948
## CowIDCow_796 0.29704
## DayDay_7 0.51841
## DayDay_9 0.31552
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.914 0.470 -18.97 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -151.98
Just looking at methanogens.
Pulling out the model for the ASVs here.
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_184 "Archaea" "Euryarchaeota" "Methanobacteria" "Methanobacteriales"
## Family Genus Species
## ASV_184 "Methanobacteriaceae" "Methanosphaera" NA
##
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i,
## link = link, phi.link = phi.link, inits = inits)
##
##
## Coefficients associated with abundance:
## Estimate Std. Error t value
## (Intercept) -5.40980 0.18307 -29.551
## Sample_TypeStomach Tube 0.02828 0.17737 0.159
## Sample_TypeLiquid Strained -0.89032 0.22933 -3.882
## Sample_TypeSolid 0.16642 0.17014 0.978
## Sample_TypeLiquid Unstrained -0.69890 0.25423 -2.749
## CowIDCow_2477 -0.46923 0.17347 -2.705
## CowIDCow_2549 -0.76002 0.19214 -3.956
## CowIDCow_796 -0.11309 0.16185 -0.699
## DayDay_7 0.05906 0.15644 0.378
## DayDay_9 -0.02356 0.15212 -0.155
## Pr(>|t|)
## (Intercept) < 0.0000000000000002 ***
## Sample_TypeStomach Tube 0.874046
## Sample_TypeLiquid Strained 0.000336 ***
## Sample_TypeSolid 0.333253
## Sample_TypeLiquid Unstrained 0.008573 **
## CowIDCow_2477 0.009610 **
## CowIDCow_2549 0.000268 ***
## CowIDCow_796 0.488308
## DayDay_7 0.707568
## DayDay_9 0.877614
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Coefficients associated with dispersion:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.6642 0.2631 -29.13 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Log-likelihood: -185.92
Checking to see what samples Methanimicrococcus is found in.
## Taxonomy Table: [1 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class Order
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia" "Methanosarcinales"
## Family Genus Species
## ASV_5594 "Methanosarcinaceae" "Methanimicrococcus" NA
## [1] Liquid Strained Solid
## Levels: Liquid Strained Solid
## OTU Table: [1 taxa and 2 samples]
## taxa are rows
## 309 389
## ASV_5594 1 1
Based on the analysis above it would see that transfaunation by getting a stomach tube sample would be close to getting a full community into the sick cow. However, if you strain the sample you will bias the communities that your transfaunation gives.
For this I can think we can just reference the phyla graphs in the “Abundance of Phyla” section. Also we will take a look more specifically at the taxa that the stomach tube samples have in common.
There are 4019 ASVs in Stomach tube samples, but only 255 taxa are present in all stomach tube samples. Due to the variability of stomach tube samples I suspect that with more sampls you will have reduce taxa in common. Stomach tube samples are composed of 20 phyla, 65 orders, 98 families and 236 genera.
## NULL
## [1] "Families in grab samples not in stomach tube"
## [1] "Sellimonas" "Incertae_Sedis" "Sarcina"
## [4] "Rhodobacter" "Ketogulonicigenium" "Sphingobium"
## [7] "Sphingobacterium" "Rikenella" "Dyadobacter"
## [10] "GCA-900066225" "UBA1819" "Oscillibacter"
## [1] "Families in stomach tube samples not in grab samples"
## [1] "Coprococcus_3" "Lachnospiraceae_NC2004_group"
## [3] "Cellulosilyticum" "Clostridioides"
## [5] "Filifactor" "Parvimonas"
## [7] "Gallicola" "Kandleria"
## [9] "Jeotgalibaca" "Aeribacillus"
## [11] "Cellvibrio" "Alysiella"
## [13] "Xylophilus" "Verticia"
## [15] "Oligella" "Moraxella"
## [17] "Caviibacter" "Bilophila"
## [19] "Bifidobacterium" "Rathayibacter"
## [21] "Curtobacterium" "Clavibacter"
## [23] "Leucobacter" "Kocuria"
## [25] "Parvibacter" "Harryflintia"
## [27] "Fournierella" "Oscillospira"
## [1] "Sellimonas" "Incertae_Sedis" "Sarcina"
## [4] "Rhodobacter" "Ketogulonicigenium" "Sphingobium"
## [7] "Sphingobacterium" "Rikenella" "Dyadobacter"
## [10] "GCA-900066225" "UBA1819" "Oscillibacter"
These the 12 genera found in the grab sample, but not the stomach tube.
## [1] "Lachnospiraceae" "Defluviitaleaceae"
## [3] NA "Ruminococcaceae"
## [5] "Veillonellaceae" "Peptostreptococcaceae"
## [7] "Family_XIII" "Family_XI"
## [9] "Clostridiales_vadinBB60_group" "Anaeroplasmataceae"
## [11] "Erysipelotrichaceae" "Mycoplasmataceae"
## [13] "Streptococcaceae" "Leuconostocaceae"
## [15] "Lactobacillaceae" "Enterococcaceae"
## [17] "Carnobacteriaceae" "Aerococcaceae"
## [19] "Staphylococcaceae" "Planococcaceae"
## [21] "Bacillaceae" "Peptococcaceae"
## [23] "Christensenellaceae" "Clostridiaceae_1"
## [25] "Acidaminococcaceae" "Syntrophomonadaceae"
## [27] "Eubacteriaceae" "Puniceicoccaceae"
## [29] "Pedosphaeraceae" "Akkermansiaceae"
## [31] "Campylobacteraceae" "Elusimicrobiaceae"
## [33] "Pirellulaceae" "Saccharimonadaceae"
## [35] "Endomicrobiaceae" "Xanthomonadaceae"
## [37] "Pseudomonadaceae" "Succinivibrionaceae"
## [39] "Enterobacteriaceae" "Burkholderiaceae"
## [41] "Cardiobacteriaceae" "Pasteurellaceae"
## [43] "Moraxellaceae" "Desulfobulbaceae"
## [45] "Oligoflexaceae" "Paracaedibacteraceae"
## [47] "Leptotrichiaceae" "Fusobacteriaceae"
## [49] "Methanobacteriaceae" "Methanomethylophilaceae"
## [51] "Methanocorpusculaceae" "Devosiaceae"
## [53] "Sphingomonadaceae" "Rhizobiaceae"
## [55] "Beijerinckiaceae" "Caulobacteraceae"
## [57] "Desulfovibrionaceae" "Desulfuromonadaceae"
## [59] "Spirochaetaceae" "vadinBE97"
## [61] "Victivallaceae" "Beutenbergiaceae"
## [63] "Microbacteriaceae" "Sanguibacteraceae"
## [65] "Corynebacteriaceae" "Nocardiaceae"
## [67] "Nocardioidaceae" "Coriobacteriales_Incertae_Sedis"
## [69] "Eggerthellaceae" "Atopobiaceae"
## [71] "Fibrobacteraceae" "Anaerolineaceae"
## [73] "0319-6G20" "Synergistaceae"
## [75] "Prevotellaceae" "Bacteroidales_UCG-001"
## [77] "Bacteroidaceae" "p-251-o5"
## [79] "Muribaculaceae" "Marinifilaceae"
## [81] "F082" "Rikenellaceae"
## [83] "Bacteroidetes_BD2-2" "Sphingobacteriaceae"
## [85] "PeH15" "M2PB4-65_termite_group"
## [87] "Bacteroidales_BS11_gut_group" "COB_P4-1_termite_group"
## [89] "Marinilabiliaceae" "Tannerellaceae"
## [91] "Paludibacteraceae" "Porphyromonadaceae"
## [93] "Bacteroidales_RF16_group"
## [1] "Lachnospiraceae_AC2044_group"
## [2] NA
## [3] "Lachnospiraceae_NK4A136_group"
## [4] "Lachnospiraceae_FE2018_group"
## [5] "Lachnospiraceae_ND3007_group"
## [6] "Acetatifactor"
## [7] "Acetitomaculum"
## [8] "Oribacterium"
## [9] "Howardella"
## [10] "Lachnospiraceae_UCG-009"
## [11] "Dorea"
## [12] "Marvinbryantia"
## [13] "Lachnoclostridium_10"
## [14] "Fusicatenibacter"
## [15] "Blautia"
## [16] "Lachnospiraceae_NK3A20_group"
## [17] "Lachnospiraceae_XPB1014_group"
## [18] "Lachnospiraceae_UCG-006"
## [19] "XBB1006"
## [20] "Roseburia"
## [21] "Shuttleworthia"
## [22] "Lachnoclostridium"
## [23] "FD2005"
## [24] "Agathobacter"
## [25] "Lachnospiraceae_UCG-001"
## [26] "Pseudobutyrivibrio"
## [27] "Tyzzerella_4"
## [28] "Moryella"
## [29] "Lachnospiraceae_UCG-002"
## [30] "Syntrophococcus"
## [31] "Butyrivibrio_2"
## [32] "Lachnoclostridium_1"
## [33] "Butyrivibrio"
## [34] "Anaerosporobacter"
## [35] "Lachnoclostridium_12"
## [36] "Lachnospira"
## [37] "Lachnospiraceae_FCS020_group"
## [38] "Lachnospiraceae_UCG-008"
## [39] "Lachnospiraceae_NK4B4_group"
## [40] "Coprococcus_2"
## [41] "Defluviitaleaceae_UCG-011"
## [42] "Lachnospiraceae_UCG-010"
## [43] "Tyzzerella"
## [44] "Coprococcus_1"
## [45] "GCA-900066575"
## [46] "Ruminococcaceae_UCG-014"
## [47] "Tyzzerella_3"
## [48] "Candidatus_Soleaferrea"
## [49] "Megasphaera"
## [50] "Veillonellaceae_UCG-001"
## [51] "Quinella"
## [52] "Selenomonas_1"
## [53] "Schwartzia"
## [54] "Selenomonas_4"
## [55] "Anaerovibrio"
## [56] "Romboutsia"
## [57] "Family_XIII_AD3011_group"
## [58] "Mogibacterium"
## [59] "Anaerovorax"
## [60] "Family_XIII_UCG-001"
## [61] "Murdochiella"
## [62] "Helcococcus"
## [63] "Peptoniphilus"
## [64] "Anaeroplasma"
## [65] "Catenisphaera"
## [66] "Erysipelotrichaceae_UCG-006"
## [67] "Solobacterium"
## [68] "Erysipelotrichaceae_UCG-009"
## [69] "Erysipelotrichaceae_UCG-008"
## [70] "Erysipelotrichaceae_UCG-004"
## [71] "Erysipelatoclostridium"
## [72] "Mycoplasma"
## [73] "Streptococcus"
## [74] "Weissella"
## [75] "Lactobacillus"
## [76] "Enterococcus"
## [77] "Desemzia"
## [78] "Aerococcus"
## [79] "Turicibacter"
## [80] "Staphylococcus"
## [81] "Planococcus"
## [82] "Clostridium_sensu_stricto_1"
## [83] "Phascolarctobacterium"
## [84] "Succiniclasticum"
## [85] "Pelospora"
## [86] "Eubacterium"
## [87] "Anaerofustis"
## [88] "Akkermansia"
## [89] "Campylobacter"
## [90] "Elusimicrobium"
## [91] "p-1088-a5_gut_group"
## [92] "Pirellula"
## [93] "CPla-4_termite_group"
## [94] "Candidatus_Saccharimonas"
## [95] "Candidatus_Endomicrobium"
## [96] "Thermomonas"
## [97] "Stenotrophomonas"
## [98] "Pseudomonas"
## [99] "Succinimonas"
## [100] "Anaerobiospirillum"
## [101] "Succinivibrio"
## [102] "Pantoea"
## [103] "Klebsiella"
## [104] "Sutterella"
## [105] "Variovorax"
## [106] "Limnohabitans"
## [107] "Comamonas"
## [108] "Janthinobacterium"
## [109] "Massilia"
## [110] "Duganella"
## [111] "Suttonella"
## [112] "Bibersteinia"
## [113] "Actinobacillus"
## [114] "Escherichia/Shigella"
## [115] "Ruminobacter"
## [116] "Psychrobacter"
## [117] "Acinetobacter"
## [118] "Succinivibrionaceae_UCG-002"
## [119] "Desulfobulbus"
## [120] "Leptotrichia"
## [121] "Fusobacterium"
## [122] "Methanobrevibacter"
## [123] "Methanosphaera"
## [124] "Candidatus_Methanomethylophilus"
## [125] "Methanocorpusculum"
## [126] "Devosia"
## [127] "Sphingomonas"
## [128] "Novosphingobium"
## [129] "Ochrobactrum"
## [130] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [131] "Neorhizobium"
## [132] "Chelativorans"
## [133] "Methylobacterium"
## [134] "Brevundimonas"
## [135] "Desulfovibrio"
## [136] "Mailhella"
## [137] "Desulfuromonas"
## [138] "M2PT2-76_termite_group"
## [139] "Sediminispirochaeta"
## [140] "Treponema_2"
## [141] "Salana"
## [142] "Pseudoclavibacter"
## [143] "Galbitalea"
## [144] "Frigoribacterium"
## [145] "Sanguibacter"
## [146] "Corynebacterium_1"
## [147] "Corynebacterium"
## [148] "Rhodococcus"
## [149] "Aeromicrobium"
## [150] "Raoultibacter"
## [151] "Denitrobacterium"
## [152] "DNF00809"
## [153] "Slackia"
## [154] "Atopobium"
## [155] "Olsenella"
## [156] "Fibrobacter"
## [157] "Flexilinea"
## [158] "Synergistes"
## [159] "Fretibacterium"
## [160] "Pyramidobacter"
## [161] "Christensenellaceae_R-7_group"
## [162] "Ruminococcaceae_UCG-010"
## [163] "Prevotellaceae_UCG-003"
## [164] "Alloprevotella"
## [165] "Prevotellaceae_UCG-004"
## [166] "Prevotellaceae_UCG-001"
## [167] "Prevotellaceae_Ga6A1_group"
## [168] "Prevotella_1"
## [169] "Prevotellaceae_NK3B31_group"
## [170] "Prevotellaceae_YAB2003_group"
## [171] "Bacteroides"
## [172] "Rikenellaceae_RC9_gut_group"
## [173] "dgA-11_gut_group"
## [174] "U29-B03"
## [175] "Pedobacter"
## [176] "Alistipes"
## [177] "Tannerella"
## [178] "Parabacteroides"
## [179] "Porphyromonas"
## [180] "hoa5-07d05_gut_group"
## [181] "Ruminiclostridium_6"
## [182] "Ruminococcus_1"
## [183] "Angelakisella"
## [184] "Ruminiclostridium"
## [185] "Hydrogenoanaerobacterium"
## [186] "Subdoligranulum"
## [187] "Caproiciproducens"
## [188] "Ruminococcus_2"
## [189] "Ruminococcaceae_UCG-001"
## [190] "Ruminiclostridium_5"
## [191] "CAG-352"
## [192] "Saccharofermentans"
## [193] "Ruminiclostridium_1"
## [194] "Ruminococcaceae_UCG-012"
## [195] "Ruminococcaceae_UCG-013"
## [196] "Ruminococcaceae_UCG-009"
## [197] "Ruminococcaceae_NK4A214_group"
## [198] "Papillibacter"
## [199] "Ruminococcaceae_UCG-007"
## [200] "Ruminococcaceae_V9D2013_group"
## [201] "Sporobacter"
## [202] "Ruminococcaceae_UCG-005"
## [203] "Ruminococcaceae_UCG-004"
## [204] "Ruminococcaceae_UCG-002"
## [205] "Ruminiclostridium_9"
## [206] "Flavonifractor"
## [207] "possible_genus_Sk018"
## [208] "probable_genus_10"
These are the 208 genera that are found in both the grab sample and stomach tube.
There are 255 ASVs are found in the grab samples, but not found in the stomach tube samples and 404 are found in the stomach tube samples, but not found in the grab samples. There is also 3615 ASVs found in common between grab samples and stomach tube samples. Let’s check at a higher taxonomic rank next.
Let’s compare the stomach tube samples to the “gold standard” of grab sample.
There are 199 ASVs and 43 genera and 13 significant differentially abundant between stomach tube and grab samples.
| x |
|---|
| Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group |
| Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group |
| Firmicutes_Lachnospiraceae_Acetatifactor |
| Firmicutes_Lachnospiraceae_Oribacterium |
| Firmicutes_Lachnospiraceae_Howardella |
| Firmicutes_Lachnospiraceae_Blautia |
| Firmicutes_Lachnospiraceae_XBB1006 |
| Firmicutes_Lachnospiraceae_Shuttleworthia |
| Firmicutes_Lachnospiraceae_Pseudobutyrivibrio |
| Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group_bacterium |
| Firmicutes_Lachnospiraceae_Butyrivibrio_2 |
| Firmicutes_Lachnospiraceae_Acetitomaculum |
| Firmicutes_Lachnospiraceae_Lachnoclostridium_10 |
| Firmicutes_Lachnospiraceae_Coprococcus_2 |
| Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group_bacterium |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014 |
| Firmicutes_Family_XIII_Mogibacterium |
| Firmicutes_Erysipelotrichaceae_Catenisphaera |
| Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009 |
| Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004 |
| Firmicutes_Streptococcaceae_Streptococcus |
| Firmicutes_Lactobacillaceae_Lactobacillus |
| Proteobacteria_Cardiobacteriaceae_Suttonella |
| Euryarchaeota_Methanobacteriaceae_Methanobrevibacter |
| Spirochaetes_Spirochaetaceae_Sediminispirochaeta |
| Actinobacteria_Atopobiaceae_Olsenella |
| Fibrobacteres_Fibrobacteraceae_Fibrobacter_succinogenes |
| Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003 |
| Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group |
| Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group |
| Firmicutes_Ruminococcaceae_Ruminococcus_1 |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001 |
| Firmicutes_Ruminococcaceae_Ruminococcus_2 |
| Firmicutes_Ruminococcaceae_CAG-352 |
| Firmicutes_Ruminococcaceae_Saccharofermentans |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013 |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group |
| Firmicutes_Ruminococcaceae_Ruminiclostridium_9 |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group |
| Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004 |
| Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group |
| Firmicutes_Lachnospiraceae_possible_genus_Sk018 |
| Firmicutes_Lachnospiraceae_probable_genus_10 |
These are the the unique genera that are significant differentially abundant between grab and stomach tube samples.
| Var1 | Freq |
|---|---|
| Firmicutes_Lachnospiraceae | 54 |
| Firmicutes_Ruminococcaceae | 31 |
| Bacteroidetes_Prevotellaceae | 25 |
| Firmicutes_Christensenellaceae | 17 |
| Fibrobacteres_Fibrobacteraceae | 16 |
| Bacteroidetes_Rikenellaceae | 8 |
| Spirochaetes_Spirochaetaceae | 8 |
| Euryarchaeota_Methanobacteriaceae | 4 |
| Firmicutes_Erysipelotrichaceae | 4 |
| Kiritimatiellaeota | 4 |
| Lentisphaerae_vadinBE97 | 4 |
| Bacteroidetes_F082 | 3 |
| Firmicutes_Family_XIII | 3 |
| Actinobacteria_Atopobiaceae | 2 |
| Bacteroidetes_Bacteroidales_BS11_gut_group | 2 |
| Actinobacteria_Eggerthellaceae | 1 |
| Bacteroidetes | 1 |
| Bacteroidetes_Bacteroidales_RF16_group | 1 |
| Bacteroidetes_Bacteroidetes_BD2-2 | 1 |
| Bacteroidetes_Muribaculaceae | 1 |
| Bacteroidetes_p-251-o5 | 1 |
| Cyanobacteria | 1 |
| Euryarchaeota_Methanomethylophilaceae | 1 |
| Firmicutes_Streptococcaceae | 1 |
| Patescibacteria | 1 |
| Proteobacteria_Burkholderiaceae | 1 |
| Proteobacteria_Succinivibrionaceae | 1 |
| Tenericutes | 1 |
| Verrucomicrobia | 1 |
From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to have significant differentially abundant ASVs in grab vs stomach tube samples. We will take a closer look at all ASVs differentially abundant.
##
## -1 1
## 21 10
This is the number of ASVs in the family Lachnospiraceae that are positively and negatively associated in stomach tube samples.
##
## -1 1
## 15 3
| x | Family | Genus | |
|---|---|---|---|
| 7 | -1.3060006 | Lachnospiraceae | XBB1006 |
| 3 | -1.2804052 | Lachnospiraceae | Acetatifactor |
| 13 | -1.0189351 | Lachnospiraceae | Lachnoclostridium_10 |
| 14 | -0.9426866 | Lachnospiraceae | Coprococcus_2 |
| 15 | -0.9321014 | Lachnospiraceae | Lachnospiraceae_FCS020_group |
| 18 | -0.9037477 | Lachnospiraceae | probable_genus_10 |
| 1 | -0.8064012 | Lachnospiraceae | Lachnospiraceae_ND3007_group |
| 8 | -0.7601064 | Lachnospiraceae | Shuttleworthia |
| 10 | -0.7250690 | Lachnospiraceae | Lachnospiraceae_AC2044_group |
| 2 | -0.6223167 | Lachnospiraceae | Lachnospiraceae_NK4A136_group |
| 9 | -0.5251488 | Lachnospiraceae | Pseudobutyrivibrio |
| 17 | -0.4515620 | Lachnospiraceae | possible_genus_Sk018 |
| 11 | -0.2900656 | Lachnospiraceae | Butyrivibrio_2 |
| 16 | -0.2899893 | Lachnospiraceae | Lachnospiraceae_XPB1014_group |
| 4 | -0.2788123 | Lachnospiraceae | Oribacterium |
| 6 | 0.3521225 | Lachnospiraceae | Blautia |
| 12 | 0.3915896 | Lachnospiraceae | Acetitomaculum |
| 5 | 1.8266653 | Lachnospiraceae | Howardella |
Going to check if there are an Euryarchaeota that are only found in one sample type.
## Taxonomy Table: [32 taxa by 7 taxonomic ranks]:
## Kingdom Phylum Class
## ASV_1308 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1441 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4053 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5508 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_7 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_184 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3038 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3184 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_264 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_710 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4546 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4863 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_24 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1749 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_88 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1703 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_84 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1323 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_484 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_599 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3860 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1114 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_948 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_700 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3066 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_54 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5586 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_58 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3936 "Archaea" "Euryarchaeota" "Thermoplasmata"
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_1434 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_4298 "Archaea" "Euryarchaeota" "Methanomicrobia"
## Order Family
## ASV_1308 "Methanobacteriales" "Methanobacteriaceae"
## ASV_1441 "Methanobacteriales" "Methanobacteriaceae"
## ASV_4053 "Methanobacteriales" "Methanobacteriaceae"
## ASV_5508 "Methanobacteriales" "Methanobacteriaceae"
## ASV_7 "Methanobacteriales" "Methanobacteriaceae"
## ASV_184 "Methanobacteriales" "Methanobacteriaceae"
## ASV_3038 "Methanobacteriales" "Methanobacteriaceae"
## ASV_3184 "Methanobacteriales" "Methanobacteriaceae"
## ASV_264 "Methanobacteriales" "Methanobacteriaceae"
## ASV_710 "Methanobacteriales" "Methanobacteriaceae"
## ASV_4546 "Methanobacteriales" "Methanobacteriaceae"
## ASV_4863 "Methanobacteriales" "Methanobacteriaceae"
## ASV_24 "Methanobacteriales" "Methanobacteriaceae"
## ASV_1749 "Methanobacteriales" "Methanobacteriaceae"
## ASV_88 "Methanobacteriales" "Methanobacteriaceae"
## ASV_1703 "Methanobacteriales" "Methanobacteriaceae"
## ASV_84 "Methanobacteriales" "Methanobacteriaceae"
## ASV_1323 "Methanobacteriales" "Methanobacteriaceae"
## ASV_484 "Methanobacteriales" "Methanobacteriaceae"
## ASV_599 "Methanobacteriales" "Methanobacteriaceae"
## ASV_3860 "Methanobacteriales" "Methanobacteriaceae"
## ASV_1114 "Methanobacteriales" "Methanobacteriaceae"
## ASV_948 "Methanobacteriales" "Methanobacteriaceae"
## ASV_700 "Methanobacteriales" "Methanobacteriaceae"
## ASV_3066 "Methanobacteriales" "Methanobacteriaceae"
## ASV_54 "Methanobacteriales" "Methanobacteriaceae"
## ASV_5586 "Methanobacteriales" "Methanobacteriaceae"
## ASV_58 "Methanobacteriales" "Methanobacteriaceae"
## ASV_3936 "Methanomassiliicoccales" "Methanomethylophilaceae"
## ASV_5594 "Methanosarcinales" "Methanosarcinaceae"
## ASV_1434 "Methanomicrobiales" "Methanocorpusculaceae"
## ASV_4298 "Methanomicrobiales" "Methanocorpusculaceae"
## Genus Species
## ASV_1308 "Methanobrevibacter" NA
## ASV_1441 "Methanobrevibacter" NA
## ASV_4053 "Methanobrevibacter" NA
## ASV_5508 "Methanobrevibacter" NA
## ASV_7 "Methanobrevibacter" NA
## ASV_184 "Methanosphaera" NA
## ASV_3038 "Methanosphaera" NA
## ASV_3184 "Methanosphaera" NA
## ASV_264 "Methanosphaera" NA
## ASV_710 "Methanosphaera" NA
## ASV_4546 "Methanobrevibacter" NA
## ASV_4863 "Methanobrevibacter" NA
## ASV_24 "Methanobrevibacter" NA
## ASV_1749 "Methanobrevibacter" NA
## ASV_88 "Methanobrevibacter" NA
## ASV_1703 "Methanobrevibacter" NA
## ASV_84 "Methanobrevibacter" NA
## ASV_1323 "Methanobrevibacter" NA
## ASV_484 "Methanobrevibacter" NA
## ASV_599 "Methanobrevibacter" NA
## ASV_3860 "Methanobrevibacter" NA
## ASV_1114 "Methanobrevibacter" NA
## ASV_948 "Methanobrevibacter" NA
## ASV_700 "Methanobrevibacter" NA
## ASV_3066 "Methanobrevibacter" NA
## ASV_54 "Methanobrevibacter" NA
## ASV_5586 "Methanobrevibacter" NA
## ASV_58 "Methanobrevibacter" NA
## ASV_3936 "Candidatus_Methanomethylophilus" NA
## ASV_5594 "Methanimicrococcus" NA
## ASV_1434 "Methanocorpusculum" NA
## ASV_4298 "Methanocorpusculum" NA
## [1] Stomach Tube Stomach Tube Stomach Tube
## [4] Stomach Tube Stomach Tube Stomach Tube
## [7] Stomach Tube Stomach Tube Stomach Tube
## [10] Stomach Tube Stomach Tube Grab Sample
## [13] Grab Sample Grab Sample Grab Sample
## [16] Grab Sample Grab Sample Grab Sample
## [19] Grab Sample Grab Sample Grab Sample
## [22] Grab Sample Grab Sample Liquid Strained
## [25] Liquid Strained Liquid Strained Liquid Strained
## [28] Liquid Strained Liquid Strained Liquid Strained
## [31] Stomach Tube Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces Feces
## [40] Feces Solid Solid
## [43] Solid Solid Solid
## [46] Solid Solid Solid
## [49] Solid Solid Solid
## [52] Solid Liquid Strained Liquid Strained
## [55] Liquid Strained Liquid Strained Liquid Strained
## [58] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained
## OTU Table: [1 taxa and 59 samples]
## taxa are rows
## 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_231 18 30 10 12 16 4 11 6 12 9 13 17 6 4 9 10
## 298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_231 8 16 16 10 6 11 6 14 6 7 30 23 22 5 10 12
## 360 361 362 363 365 368 371 373 379 380 381 382 383 384 385 386
## ASV_231 17 17 14 8 19 2 1 1 25 38 15 45 18 24 15 53
## 387 388 389 390 505 506 507 508 509 510 511
## ASV_231 38 23 34 6 9 19 8 2 63 42 35
These are the genera that are significant differentially abundant genera in stomach tube vs grab samples.
## [1] NA "Fibrobacter"
The only assigned genera in the family Fibrobacteraceae, Fibrobacter was significantly lower in abundance in stomach tubes compared to grab samples.
| x | Phylum | Family | Genus |
|---|---|---|---|
| -1.8769355 | Fibrobacteres | Fibrobacteraceae | Fibrobacter |
| -1.3060006 | Firmicutes | Lachnospiraceae | XBB1006 |
| -1.2804052 | Firmicutes | Lachnospiraceae | Acetatifactor |
| -1.0189351 | Firmicutes | Lachnospiraceae | Lachnoclostridium_10 |
| -0.9426866 | Firmicutes | Lachnospiraceae | Coprococcus_2 |
| -0.9321014 | Firmicutes | Lachnospiraceae | Lachnospiraceae_FCS020_group |
| -0.9037477 | Firmicutes | Lachnospiraceae | probable_genus_10 |
| -0.8739379 | Bacteroidetes | Prevotellaceae | Prevotellaceae_Ga6A1_group |
| -0.8064012 | Firmicutes | Lachnospiraceae | Lachnospiraceae_ND3007_group |
| -0.7661424 | Firmicutes | Ruminococcaceae | Ruminococcus_1 |
| -0.7601064 | Firmicutes | Lachnospiraceae | Shuttleworthia |
| -0.7250690 | Firmicutes | Lachnospiraceae | Lachnospiraceae_AC2044_group |
| -0.7159013 | Spirochaetes | Spirochaetaceae | Sediminispirochaeta |
| -0.6223167 | Firmicutes | Lachnospiraceae | Lachnospiraceae_NK4A136_group |
| -0.5577767 | Bacteroidetes | Prevotellaceae | Prevotellaceae_NK3B31_group |
| -0.5251488 | Firmicutes | Lachnospiraceae | Pseudobutyrivibrio |
| -0.4677556 | Firmicutes | Ruminococcaceae | Saccharofermentans |
| -0.4515620 | Firmicutes | Lachnospiraceae | possible_genus_Sk018 |
| -0.3024765 | Firmicutes | Ruminococcaceae | Ruminococcaceae_UCG-014 |
| -0.2900656 | Firmicutes | Lachnospiraceae | Butyrivibrio_2 |
| -0.2899893 | Firmicutes | Lachnospiraceae | Lachnospiraceae_XPB1014_group |
| -0.2788123 | Firmicutes | Lachnospiraceae | Oribacterium |
| 0.3193401 | Euryarchaeota | Methanobacteriaceae | Methanobrevibacter |
| 0.3521225 | Firmicutes | Lachnospiraceae | Blautia |
| 0.3735289 | Firmicutes | Family_XIII | Mogibacterium |
| 0.3767681 | Bacteroidetes | Prevotellaceae | Prevotellaceae_UCG-003 |
| 0.3915896 | Firmicutes | Lachnospiraceae | Acetitomaculum |
| 0.4050196 | Firmicutes | Ruminococcaceae | Ruminococcaceae_NK4A214_group |
| 0.4068741 | Firmicutes | Ruminococcaceae | Ruminococcaceae_UCG-004 |
| 0.4091719 | Firmicutes | Ruminococcaceae | Ruminococcus_2 |
| 0.4213922 | Firmicutes | Ruminococcaceae | Ruminococcaceae_V9D2013_group |
| 0.6291728 | Firmicutes | Erysipelotrichaceae | Catenisphaera |
| 0.7125459 | Firmicutes | Ruminococcaceae | Ruminococcaceae_UCG-001 |
| 0.7537462 | Actinobacteria | Atopobiaceae | Olsenella |
| 0.7998338 | Firmicutes | Lactobacillaceae | Lactobacillus |
| 0.9805989 | Firmicutes | Erysipelotrichaceae | Erysipelotrichaceae_UCG-009 |
| 1.0394506 | Firmicutes | Ruminococcaceae | Ruminococcaceae_UCG-013 |
| 1.1037244 | Firmicutes | Ruminococcaceae | Ruminiclostridium_9 |
| 1.1678026 | Firmicutes | Erysipelotrichaceae | Erysipelotrichaceae_UCG-004 |
| 1.5268279 | Firmicutes | Ruminococcaceae | CAG-352 |
| 1.6367580 | Proteobacteria | Cardiobacteriaceae | Suttonella |
| 1.8266653 | Firmicutes | Lachnospiraceae | Howardella |
| 1.8417467 | Firmicutes | Streptococcaceae | Streptococcus |
Let’s compare the liquid strained samples to the “gold standard” of grab sample.
There are 283 ASVs are found in the grab sample, but not found in the liquid strained samples. There is also 3587 ASVs found in common between grab samples. Thus, stomach tube samples tend to be more like a grab sample than a strained sample. Let’s check at a higher taxonomic rank next.
## [1] "Sellimonas" "Tyzzerella"
## [3] "Desemzia" "Limnohabitans"
## [5] "Leptotrichia" "Salana"
## [7] "Rikenella" "GCA-900066225"
## [9] "Hydrogenoanaerobacterium"
These genera are found in the grab sample, but not the stomach tube.
## [1] "Lachnospiraceae_AC2044_group"
## [2] NA
## [3] "Lachnospiraceae_NK4A136_group"
## [4] "Lachnospiraceae_FE2018_group"
## [5] "Lachnospiraceae_ND3007_group"
## [6] "Acetatifactor"
## [7] "Acetitomaculum"
## [8] "Oribacterium"
## [9] "Howardella"
## [10] "Lachnospiraceae_UCG-009"
## [11] "Dorea"
## [12] "Marvinbryantia"
## [13] "Lachnoclostridium_10"
## [14] "Fusicatenibacter"
## [15] "Blautia"
## [16] "Lachnospiraceae_NK3A20_group"
## [17] "Lachnospiraceae_XPB1014_group"
## [18] "Lachnospiraceae_UCG-006"
## [19] "XBB1006"
## [20] "Roseburia"
## [21] "Shuttleworthia"
## [22] "Lachnoclostridium"
## [23] "FD2005"
## [24] "Agathobacter"
## [25] "Lachnospiraceae_UCG-001"
## [26] "Pseudobutyrivibrio"
## [27] "Tyzzerella_4"
## [28] "Moryella"
## [29] "Lachnospiraceae_UCG-002"
## [30] "Syntrophococcus"
## [31] "Butyrivibrio_2"
## [32] "Lachnoclostridium_1"
## [33] "Butyrivibrio"
## [34] "Anaerosporobacter"
## [35] "Lachnoclostridium_12"
## [36] "Lachnospira"
## [37] "Lachnospiraceae_FCS020_group"
## [38] "Lachnospiraceae_UCG-008"
## [39] "Lachnospiraceae_NK4B4_group"
## [40] "Coprococcus_2"
## [41] "Defluviitaleaceae_UCG-011"
## [42] "Lachnospiraceae_UCG-010"
## [43] "Coprococcus_1"
## [44] "GCA-900066575"
## [45] "Incertae_Sedis"
## [46] "Ruminococcaceae_UCG-014"
## [47] "Tyzzerella_3"
## [48] "Candidatus_Soleaferrea"
## [49] "Megasphaera"
## [50] "Veillonellaceae_UCG-001"
## [51] "Quinella"
## [52] "Selenomonas_1"
## [53] "Schwartzia"
## [54] "Selenomonas_4"
## [55] "Anaerovibrio"
## [56] "Romboutsia"
## [57] "Family_XIII_AD3011_group"
## [58] "Mogibacterium"
## [59] "Anaerovorax"
## [60] "Family_XIII_UCG-001"
## [61] "Murdochiella"
## [62] "Helcococcus"
## [63] "Peptoniphilus"
## [64] "Anaeroplasma"
## [65] "Catenisphaera"
## [66] "Erysipelotrichaceae_UCG-006"
## [67] "Solobacterium"
## [68] "Erysipelotrichaceae_UCG-009"
## [69] "Erysipelotrichaceae_UCG-008"
## [70] "Erysipelotrichaceae_UCG-004"
## [71] "Erysipelatoclostridium"
## [72] "Mycoplasma"
## [73] "Streptococcus"
## [74] "Weissella"
## [75] "Lactobacillus"
## [76] "Enterococcus"
## [77] "Aerococcus"
## [78] "Turicibacter"
## [79] "Staphylococcus"
## [80] "Planococcus"
## [81] "Clostridium_sensu_stricto_1"
## [82] "Sarcina"
## [83] "Phascolarctobacterium"
## [84] "Succiniclasticum"
## [85] "Pelospora"
## [86] "Eubacterium"
## [87] "Anaerofustis"
## [88] "Akkermansia"
## [89] "Campylobacter"
## [90] "Elusimicrobium"
## [91] "p-1088-a5_gut_group"
## [92] "Pirellula"
## [93] "CPla-4_termite_group"
## [94] "Candidatus_Saccharimonas"
## [95] "Candidatus_Endomicrobium"
## [96] "Thermomonas"
## [97] "Stenotrophomonas"
## [98] "Pseudomonas"
## [99] "Succinimonas"
## [100] "Anaerobiospirillum"
## [101] "Succinivibrio"
## [102] "Pantoea"
## [103] "Klebsiella"
## [104] "Sutterella"
## [105] "Variovorax"
## [106] "Comamonas"
## [107] "Janthinobacterium"
## [108] "Massilia"
## [109] "Duganella"
## [110] "Suttonella"
## [111] "Bibersteinia"
## [112] "Actinobacillus"
## [113] "Escherichia/Shigella"
## [114] "Ruminobacter"
## [115] "Psychrobacter"
## [116] "Acinetobacter"
## [117] "Succinivibrionaceae_UCG-002"
## [118] "Desulfobulbus"
## [119] "Fusobacterium"
## [120] "Methanobrevibacter"
## [121] "Methanosphaera"
## [122] "Candidatus_Methanomethylophilus"
## [123] "Methanocorpusculum"
## [124] "Rhodobacter"
## [125] "Ketogulonicigenium"
## [126] "Devosia"
## [127] "Sphingomonas"
## [128] "Novosphingobium"
## [129] "Sphingobium"
## [130] "Ochrobactrum"
## [131] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [132] "Neorhizobium"
## [133] "Chelativorans"
## [134] "Methylobacterium"
## [135] "Brevundimonas"
## [136] "Desulfovibrio"
## [137] "Mailhella"
## [138] "Desulfuromonas"
## [139] "M2PT2-76_termite_group"
## [140] "Sediminispirochaeta"
## [141] "Treponema_2"
## [142] "Pseudoclavibacter"
## [143] "Galbitalea"
## [144] "Frigoribacterium"
## [145] "Sanguibacter"
## [146] "Corynebacterium_1"
## [147] "Corynebacterium"
## [148] "Rhodococcus"
## [149] "Aeromicrobium"
## [150] "Raoultibacter"
## [151] "Denitrobacterium"
## [152] "DNF00809"
## [153] "Slackia"
## [154] "Atopobium"
## [155] "Olsenella"
## [156] "Fibrobacter"
## [157] "Flexilinea"
## [158] "Synergistes"
## [159] "Fretibacterium"
## [160] "Pyramidobacter"
## [161] "Christensenellaceae_R-7_group"
## [162] "Ruminococcaceae_UCG-010"
## [163] "Prevotellaceae_UCG-003"
## [164] "Alloprevotella"
## [165] "Prevotellaceae_UCG-004"
## [166] "Prevotellaceae_UCG-001"
## [167] "Prevotellaceae_Ga6A1_group"
## [168] "Prevotella_1"
## [169] "Prevotellaceae_NK3B31_group"
## [170] "Prevotellaceae_YAB2003_group"
## [171] "Bacteroides"
## [172] "Rikenellaceae_RC9_gut_group"
## [173] "dgA-11_gut_group"
## [174] "U29-B03"
## [175] "Sphingobacterium"
## [176] "Pedobacter"
## [177] "Alistipes"
## [178] "Dyadobacter"
## [179] "Tannerella"
## [180] "Parabacteroides"
## [181] "Porphyromonas"
## [182] "hoa5-07d05_gut_group"
## [183] "Ruminiclostridium_6"
## [184] "Ruminococcus_1"
## [185] "Angelakisella"
## [186] "Ruminiclostridium"
## [187] "Subdoligranulum"
## [188] "UBA1819"
## [189] "Caproiciproducens"
## [190] "Ruminococcus_2"
## [191] "Ruminococcaceae_UCG-001"
## [192] "Ruminiclostridium_5"
## [193] "CAG-352"
## [194] "Saccharofermentans"
## [195] "Ruminiclostridium_1"
## [196] "Ruminococcaceae_UCG-012"
## [197] "Ruminococcaceae_UCG-013"
## [198] "Ruminococcaceae_UCG-009"
## [199] "Ruminococcaceae_NK4A214_group"
## [200] "Papillibacter"
## [201] "Ruminococcaceae_UCG-007"
## [202] "Ruminococcaceae_V9D2013_group"
## [203] "Sporobacter"
## [204] "Ruminococcaceae_UCG-005"
## [205] "Ruminococcaceae_UCG-004"
## [206] "Oscillibacter"
## [207] "Ruminococcaceae_UCG-002"
## [208] "Ruminiclostridium_9"
## [209] "Flavonifractor"
## [210] "possible_genus_Sk018"
## [211] "probable_genus_10"
These are the 211 genera that are found in both the grab sample and liquid strained samples.
Since we saw that liquid strained samples were distinguished from other rumen samples by Kiritimatiellaeota on the DPCoA we will investigate that further.
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 180 taxa and 68 samples ]
## sample_data() Sample Data: [ 68 samples by 9 sample variables ]
## tax_table() Taxonomy Table: [ 180 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 180 tips and 179 internal nodes ]
## [1] "Kiritimatiellae_WCHB1-41"
There are 180 ASVs assigned to the phylum Kiritimatiellaeota and these ASVs are only assigned down to the order level. Due to this you won’t find these taxa in the corncob data that was run on genera.
## [1] Stomach Tube Stomach Tube Stomach Tube
## [4] Stomach Tube Stomach Tube Stomach Tube
## [7] Stomach Tube Stomach Tube Stomach Tube
## [10] Stomach Tube Stomach Tube Grab Sample
## [13] Grab Sample Grab Sample Grab Sample
## [16] Grab Sample Grab Sample Grab Sample
## [19] Grab Sample Grab Sample Grab Sample
## [22] Grab Sample Grab Sample Liquid Strained
## [25] Liquid Strained Liquid Strained Liquid Strained
## [28] Liquid Strained Liquid Strained Liquid Strained
## [31] Stomach Tube Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces Feces
## [40] Feces Feces Feces
## [43] Feces Feces Feces
## [46] Feces Feces Feces
## [49] Feces Solid Solid
## [52] Solid Solid Solid
## [55] Solid Solid Solid
## [58] Solid Solid Solid
## [61] Solid Liquid Strained Liquid Strained
## [64] Liquid Strained Liquid Strained Liquid Strained
## [67] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained
The phylum Kiritimatiellaeota is found in all sample types.
There are 180 ASVs assigned to the phylum Kiritimatiellaeota, 17 of these ASVs were significant differentially abundant.
| Var1 | Freq |
|---|---|
| Firmicutes_Lachnospiraceae | 25 |
| Firmicutes_Ruminococcaceae | 15 |
| Bacteroidetes_Prevotellaceae | 6 |
| Firmicutes_Veillonellaceae | 5 |
| Proteobacteria_Succinivibrionaceae | 5 |
| Firmicutes_Erysipelotrichaceae | 4 |
| Firmicutes_Family_XIII | 3 |
| Bacteroidetes_Rikenellaceae | 2 |
| Proteobacteria_Desulfovibrionaceae | 2 |
| Synergistetes_Synergistaceae | 2 |
| Actinobacteria_Atopobiaceae | 1 |
| Actinobacteria_Coriobacteriales_Incertae_Sedis | 1 |
| Actinobacteria_Eggerthellaceae | 1 |
| Elusimicrobia_Elusimicrobiaceae | 1 |
| Elusimicrobia_Endomicrobiaceae | 1 |
| Epsilonbacteraeota_Campylobacteraceae | 1 |
| Euryarchaeota_Methanobacteriaceae | 1 |
| Firmicutes_Christensenellaceae | 1 |
| Firmicutes_Defluviitaleaceae | 1 |
| Firmicutes_Eubacteriaceae | 1 |
| Firmicutes_Streptococcaceae | 1 |
| Planctomycetes_Pirellulaceae | 1 |
| Proteobacteria_Burkholderiaceae | 1 |
| Proteobacteria_Desulfobulbaceae | 1 |
| Proteobacteria_Desulfuromonadaceae | 1 |
| Proteobacteria_Pseudomonadaceae | 1 |
| Spirochaetes_Spirochaetaceae | 1 |
| Tenericutes_Anaeroplasmataceae | 1 |
Here we see again that Prevotellaceae, Lachnospiraceae and Ruminococcaceae to have genera that are the significantly differentially abundant.
| Phylum | #Significant ASVs | Total ASVs | Percent Significant ASVs |
|---|---|---|---|
| Actinobacteria | 23 | 96 | 23.958333 |
| Bacteroidetes | 56 | 1257 | 4.455052 |
| Chloroflexi | 15 | 39 | 38.461539 |
| Cyanobacteria | 6 | 65 | 9.230769 |
| Elusimicrobia | 3 | 16 | 18.750000 |
| Euryarchaeota | 16 | 44 | 36.363636 |
| Fibrobacteres | 8 | 39 | 20.512821 |
| Firmicutes | 540 | 3095 | 17.447496 |
| Kiritimatiellaeota | 17 | 180 | 9.444444 |
| Lentisphaerae | 3 | 31 | 9.677419 |
| Patescibacteria | 3 | 14 | 21.428571 |
| Proteobacteria | 11 | 219 | 5.022831 |
| Spirochaetes | 8 | 138 | 5.797101 |
| Tenericutes | 15 | 188 | 7.978723 |
| Verrucomicrobia | 1 | 35 | 2.857143 |
| Deferribacteres | 0 | 1 | 0.000000 |
| Epsilonbacteraeota | 0 | 2 | 0.000000 |
| Fusobacteria | 0 | 4 | 0.000000 |
| Gemmatimonadetes | 0 | 1 | 0.000000 |
| Planctomycetes | 0 | 15 | 0.000000 |
| Synergistetes | 0 | 6 | 0.000000 |
We also saw on the DPCoA that a group of Bacteroidetes (Prevotellaceae) was associated with the liquid strained samples. Additionally, another family in the same phylum, Lachnospiraceae, wasn’t associate with liquid strained samples.
As a reminder we can do differential abundance testing on genera and graph all the results from the phylum Bacteroidetes.
We will look further into these families to decipher what genera are causing this difference between grab and liquid samples.
##
## -1 1
## 2 4
In the family Prevotellaceae there are 2 genera significantly lower in relative abundance and 4 genera with significantly higher relative abundance in stomach tube compared to grab samples.
| x | xmin | xmax | variable | Genus |
|---|---|---|---|---|
| -1.0395575 | -1.4609369 | -0.6181780 | Liquid Strained Differential Abundance | Prevotellaceae_NK3B31_group |
| -0.6891250 | -0.9859915 | -0.3922586 | Liquid Strained Differential Abundance | Prevotellaceae_UCG-004 |
| 0.8598287 | 0.7214513 | 0.9982061 | Liquid Strained Differential Abundance | Prevotellaceae_UCG-001 |
| 1.1682901 | 0.2628093 | 2.0737709 | Liquid Strained Differential Abundance | Prevotellaceae_YAB2003_group |
| 1.1737147 | 1.0347963 | 1.3126331 | Liquid Strained Differential Abundance | Prevotellaceae_UCG-003 |
| 1.2715117 | 1.0897500 | 1.4532734 | Liquid Strained Differential Abundance | Prevotella_1 |
These are the Prevotellaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.
##
## -1 1
## 7 8
In the family Ruminococcaceae there are 7 genera significantly lower in relative abundance and 8 genera with significantly higher relative abundance in stomach tube compared to grab samples.
| x | xmin | xmax | variable | Genus |
|---|---|---|---|---|
| -1.3453328 | -2.6413920 | -0.0492735 | Liquid Strained Differential Abundance | Caproiciproducens |
| -1.2056047 | -1.3647354 | -1.0464741 | Liquid Strained Differential Abundance | Saccharofermentans |
| -0.8534209 | -1.1680016 | -0.5388402 | Liquid Strained Differential Abundance | Papillibacter |
| -0.4246426 | -0.5459944 | -0.3032907 | Liquid Strained Differential Abundance | Ruminococcus_1 |
| -0.3820756 | -0.5860149 | -0.1781363 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-005 |
| -0.2635253 | -0.4265474 | -0.1005032 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-010 |
| -0.2426040 | -0.3496181 | -0.1355899 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-014 |
| 0.2581495 | 0.1321582 | 0.3841409 | Liquid Strained Differential Abundance | Ruminococcaceae_NK4A214_group |
| 0.3558794 | 0.1207070 | 0.5910518 | Liquid Strained Differential Abundance | Ruminococcus_2 |
| 0.5051468 | 0.2751281 | 0.7351655 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-004 |
| 0.6982247 | 0.1210530 | 1.2753963 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-001 |
| 0.8095391 | 0.4188809 | 1.2001974 | Liquid Strained Differential Abundance | Ruminiclostridium_9 |
| 1.2720314 | 1.0289351 | 1.5151278 | Liquid Strained Differential Abundance | Ruminococcaceae_V9D2013_group |
| 1.6229601 | 1.2512347 | 1.9946856 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-013 |
| 1.7220503 | 1.3963081 | 2.0477924 | Liquid Strained Differential Abundance | Ruminococcaceae_UCG-002 |
These are the Ruminococcaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.
##
## -1 1
## 22 3
In the family Lachnospiraceae there are 22 genera significantly lower in relative abundance and 3 genera with significantly higher relative abundance in stomach tube compared to grab samples.
| x | xmin | xmax | variable | Genus |
|---|---|---|---|---|
| -1.6853162 | -2.8561358 | -0.5144965 | Liquid Strained Differential Abundance | Butyrivibrio |
| -1.5519291 | -1.8484651 | -1.2553931 | Liquid Strained Differential Abundance | Lachnoclostridium_10 |
| -1.3151462 | -2.3454300 | -0.2848623 | Liquid Strained Differential Abundance | Fusicatenibacter |
| -1.2927867 | -1.7671418 | -0.8184316 | Liquid Strained Differential Abundance | Coprococcus_1 |
| -1.2642825 | -1.7307755 | -0.7977896 | Liquid Strained Differential Abundance | Lachnospiraceae_UCG-002 |
| -1.2205535 | -2.2914813 | -0.1496256 | Liquid Strained Differential Abundance | Lachnoclostridium |
| -1.1866044 | -1.4115176 | -0.9616912 | Liquid Strained Differential Abundance | probable_genus_10 |
| -1.1721461 | -2.0657393 | -0.2785528 | Liquid Strained Differential Abundance | GCA-900066575 |
| -1.1635327 | -1.4643447 | -0.8627207 | Liquid Strained Differential Abundance | Lachnospiraceae_UCG-006 |
| -1.1167935 | -1.3105063 | -0.9230807 | Liquid Strained Differential Abundance | Lachnospiraceae_NK3A20_group |
| -1.1059423 | -1.7519892 | -0.4598953 | Liquid Strained Differential Abundance | Lachnospiraceae_UCG-010 |
| -1.0858461 | -1.3568485 | -0.8148437 | Liquid Strained Differential Abundance | Marvinbryantia |
| -1.0489392 | -1.3258423 | -0.7720361 | Liquid Strained Differential Abundance | Lachnospiraceae_FCS020_group |
| -0.9668531 | -1.2363998 | -0.6973064 | Liquid Strained Differential Abundance | Moryella |
| -0.9563162 | -1.6386116 | -0.2740208 | Liquid Strained Differential Abundance | Lachnospiraceae_FE2018_group |
| -0.9413635 | -1.4029512 | -0.4797758 | Liquid Strained Differential Abundance | Acetatifactor |
| -0.9388259 | -1.0801695 | -0.7974823 | Liquid Strained Differential Abundance | Lachnospiraceae_AC2044_group |
| -0.8050490 | -1.0692876 | -0.5408105 | Liquid Strained Differential Abundance | Lachnospiraceae_UCG-008 |
| -0.4973641 | -0.8497914 | -0.1449368 | Liquid Strained Differential Abundance | possible_genus_Sk018 |
| -0.4958562 | -0.6231301 | -0.3685824 | Liquid Strained Differential Abundance | Butyrivibrio_2 |
| -0.4777957 | -0.6777349 | -0.2778565 | Liquid Strained Differential Abundance | Lachnospiraceae_XPB1014_group |
| -0.4617096 | -0.6778755 | -0.2455438 | Liquid Strained Differential Abundance | Lachnospiraceae_ND3007_group |
| 0.4937215 | 0.1923139 | 0.7951290 | Liquid Strained Differential Abundance | Roseburia |
| 0.7951294 | 0.3027545 | 1.2875042 | Liquid Strained Differential Abundance | Tyzzerella_3 |
| 1.8744033 | 1.2078136 | 2.5409931 | Liquid Strained Differential Abundance | Howardella |
These are the Lachnospiraceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.
## [1] "Families in liquid strained samples not in stomach tube"
## [1] "Incertae_Sedis" "Terrisporobacter" "Breznakia"
## [4] "Allobaculum" "Jeotgalicoccus" "Proteiniclasticum"
## [7] "Sarcina" "Gilvimarinus" "Pigmentiphaga"
## [10] "Aestuariispira" "Methanimicrococcus" "Rhodobacter"
## [13] "Ketogulonicigenium" "Sphingobium" "Aureimonas"
## [16] "Pseudochrobactrum" "Glutamicibacter" "Pontibacter"
## [19] "Sphingobacterium" "Anaerocella" "Dyadobacter"
## [22] "Anaerofilum" "UBA1819" "Faecalibacterium"
## [25] "Oscillibacter"
## [1] "Families in stomach tube samples not in liquid strained samples"
## [1] "Tyzzerella" "Cellulosilyticum"
## [3] "Filifactor" "Parvimonas"
## [5] "Kandleria" "Desemzia"
## [7] "Alysiella" "Limnohabitans"
## [9] "Leptotrichia" "Salana"
## [11] "Curtobacterium" "Leucobacter"
## [13] "Harryflintia" "Hydrogenoanaerobacterium"
## [1] "Families in liquid unstrained samples not in stomach tube"
## [1] "Incertae_Sedis" "Terrisporobacter" "Paeniclostridium"
## [4] "Allobaculum" "Jeotgalicoccus" "Peptococcus"
## [7] "Proteiniclasticum" "Sarcina" "Rhodobacter"
## [10] "Pseudochrobactrum" "GWE2-31-10" "Kineococcus"
## [13] "Aeriscardovia" "Glutamicibacter" "Sphingobacterium"
## [16] "Anaerocella" "Chryseobacterium" "Gillisia"
## [19] "Rikenella" "Dyadobacter" "Hymenobacter"
## [22] "Proteiniphilum" "Negativibacillus" "Oscillibacter"
## [1] "Families in stomach tube samples not in liquid unstrained samples"
## [1] "Dorea" "Filifactor" "Parvimonas"
## [4] "Kandleria" "Desemzia" "Jeotgalibaca"
## [7] "Aeribacillus" "Alysiella" "Caviibacter"
## [10] "Leptotrichia" "Ochrobactrum" "Salana"
## [13] "Clavibacter" "Frigoribacterium" "Leucobacter"
## [16] "Aeromicrobium" "Slackia" "Synergistes"
## [19] "Tannerella" "Harryflintia"
Looking to see if stomach tubes are much different than liquid samples
Exploratory analysis of DPCoA.
This looks like liquid samples (strained mostly) differ from stomach tube samples in due to increases in Rikenellaceae, Prevotellaceae and Kiritimatiellaeota. Stomach stube samples have an increase in Christensenllaceae and Lachnospiraceae.